Content carousel in a social media timeline

ABSTRACT

Techniques of the disclosure are directed to a computing device creating and outputting, for display at client devices accessing a social media platform, targeted content. The computing device may receive candidate messages composed by users of a group of client devices, where the candidate messages each include a reference to the requisite product, brand, or market. If a candidate message has a determined interest score that satisfies a threshold interest score, the computing device includes the candidate message into a group of brand messages. The computing device may then send the targeted message to be output for display at another group of client devices, where the targeted message includes both an original portion and a carousel portion. The carousel portion includes a group of transitional windows, where each transitional window includes one of the brand messages from the group of brand messages.

This application claims the benefit of U.S. Provisional Application No.62/448,855, filed Jan. 20, 2017, the entire contents of which areincorporated by reference herein.

BACKGROUND

A social media platform leverages computing resources thatprogrammatically collect, classify, and index worldwide content, whichincludes, for example, user generated content, live streams of sportingevents, pod casts, creative content, movies, and TV/cable shows. Contentcollection includes receiving over a network, text, images, sound, andvideo, some or all of which may be previously generated and/or capturedlive via a mobile device. Content classification is implementedprogrammatically by leveraging rule engines, heuristic engines, and/ormachine learning resources. The platform indexes content based oninterest.

For user consumption, the platform provides interfaces, one of which isa timeline of content presented in reverse chronological order anddemarked by distinct messages. Instances of the timeline are generatedfor particular users or particular groups of users based oncorresponding interest and social graphs. The timelines are refreshed inreal-time and at global scale, for example, when new content isavailable and especially when an event or topic of interest is trending.

SUMMARY

In one implementation, the social media platform generates and embeds acarousel of content in a reversed chronological timeline in which a usermay consume content by scrolling up or down to introduce portions of thetimeline into a display screen. The carousel presents content related toa particular topic of interest, e.g., a breaking news event, a consumerproduct of interest, and a recently released song from a previouslyunknown artist. The carousel has content that, figuratively speaking,loops across the display screen (like a carousel, either automaticallyor by user swiping gestures) without any up or down scrolling of thetimeline, thus allowing the user to consume the content of the carouselwithout losing track of her place in the timeline. Content for thecarousel are programmatically curated by leveraging machine learningmodels, e.g., neural networks and regression models, that predictinterest based on stated preferences and historical behavior, examplesof which include clicks, follows, likes, and other engagements. Contentcurated includes user-generated content, creative content, as well asany other content available on the platform. Carousel creation for aparticular user is triggered when the platform detects a trend predictedto be of interest to the user. Like carousel content curation, trenddetection for triggering carousel creation is implemented by leveragemachine learning that predicts trends based on any combination of time(freshness), topicality, trustworthiness, geolocation, user preferencesand past actions, as well as any other feature that may inform aboutuser interest.

One compelling trigger is a trending topic about a news-breaking event,programmatically detectable by a spike in a velocity graph of a numberof messages over time. In this case, the platform generates, inreal-time and while the event is still breaking, a carousel thatincludes both user generated content and news publisher contentdescribing and commenting about the event and embeds that carousel intotimelines of users who the platform predicts would be interested.

Another compelling trigger is brand buzz reaching a threshold. In thiscase, the platform generates, in real-time and while the buzz is stillabove the threshold, a carousel that includes both creative (alsoreferred to as “original”) and user generated content related to thebranded product of interest and embeds that carousel into timelines ofusers who the platform predicts would be interested.

Alternatively, for timelines that scroll across a display screen, thecarousel loops up and down. Whatever the case, the carousel is able toloop without the timeline being scrolled so the user is able to consumeits content without losing her place in the timeline.

In some examples, a method includes receiving, by a computing device andfrom an information distribution system, a first group of one or moremessages composed by one or more users of a first group of one or moreclient devices accessing a social media platform. Each of the messagesin the first group of one or more messages includes a reference to aparticular brand. The method further includes determining, by thecomputing device, an interest score for a candidate message based atleast in part on content of the candidate message. The candidate messageis included in the first group of one or more messages. The method alsoincludes, responsive to determining that the interest score satisfies athreshold interest score, inserting, by the computing device, thecandidate message into a group of one or more brand messages. Each brandmessage in the group of one or more brand messages includes a referenceto the particular brand. The method further includes sending, by thecomputing device and to the information distribution system, a targetedmessage to be output for display at a second group of one or more clientdevices. The targeted message comprises an original portion and acarousel portion. The carousel portion comprises a group of one or moretransitional windows, where each transitional window in the group of oneor more transitional windows includes one of the brand messages in thegroup of one or more brand messages. The original portion comprisescontent formed at the computing device.

In some examples, a computing device includes at least one processor andat least one non-transitory computer-readable storage medium storinginstructions that are executable by the at least one processor toreceive, from an information distribution system, a first group of oneor more messages composed by one or more users of a first group of oneor more client devices accessing a social media platform. Each of themessages in the first group of one or more messages includes a referenceto a particular brand. The instructions are further executable by the atleast one processor to determine an interest score for a candidatemessage based at least in part on content of the candidate message. Thecandidate message is included in the first group of one or moremessages. The instructions are further executable by the at least oneprocessor to, responsive to determining that the interest scoresatisfies a threshold interest score, insert the candidate message intoa group of one or more brand messages. Each brand message in the groupof one or more brand messages includes a reference to the particularbrand. The instructions are also executable by the at least oneprocessor to send, to the information distribution system, a targetedmessage to be output for display at a second group of one or more clientdevices. The targeted message comprises an original portion and acarousel portion. The carousel portion comprises a group of one or moretransitional windows, where each transitional window in the group of oneor more transitional windows includes one of the brand messages in thegroup of one or more brand messages. The original portion comprisescontent formed at the computing device.

In some examples, a non-transitory computer-readable storage medium isencoded with instructions that, when executed, cause at least oneprocessor of a computing device to receive, from an informationdistribution system, a first group of one or more messages composed byone or more users of a first group of one or more client devicesaccessing a social media platform. Each of the messages in the firstgroup of one or more messages includes a reference to a particularbrand. The instructions further cause the computing device to determinean interest score for a candidate message based at least in part oncontent of the candidate message. The candidate message is included inthe first group of one or more messages. The instructions further causethe computing device to, responsive to determining that the interestscore satisfies a threshold interest score, insert the candidate messageinto a group of one or more brand messages. Each brand message in thegroup of one or more brand messages includes a reference to theparticular brand. The instructions also cause the computing device tosend, to the information distribution system, a targeted message to beoutput for display at a second group of one or more client devices. Thetargeted message comprises an original portion and a carousel portion.The carousel portion comprises a group of one or more transitionalwindows, where each transitional window in the group of one or moretransitional windows includes one of the brand messages in the group ofone or more brand messages. The original portion comprises contentformed at the computing device.

In some examples, an apparatus includes means for receiving, from aninformation distribution system, a first group of one or more messagescomposed by one or more users of a first group of one or more clientdevices accessing a social media platform. Each of the messages in thefirst group of one or more messages includes a reference to a particularbrand. The apparatus further includes means for determining, using amachine learning model, an interest score for a candidate message basedat least in part on content of the candidate message. The candidatemessage is included in the first group of one or more messages. Theapparatus further includes, responsive to determining that the interestscore satisfies a threshold interest score, means for inserting thecandidate message into a group of one or more brand messages. Each brandmessage in the group of one or more brand messages includes a referenceto the particular brand. The apparatus further includes means forsending, to the information distribution system, a targeted message tobe output for display at a second group of one or more client devices.The targeted message comprises an original portion and a carouselportion. The carousel portion comprises a group of one or moretransitional windows, where each transitional window in the group of oneor more transitional windows includes one of the brand messages in thegroup of one or more brand messages. The original portion comprisescontent formed at the computing device.

The above techniques may enable a computing device to create a targetedmessage that includes both an original portion and a carousel portion,rather than limiting a creator to only a single message or a singlenested message. These techniques further enable a content provider, suchas an advertiser, to include multiple forms of content, includingorganic content and user generated content, within a single targetedmessage, thereby increasing the amount of content provided to the userwithout increasing the size of the content on the screen of the user'scomputing device. In some instances, media may be more effective inconveying information regarding a product. In other instances,user-generated content created by a party influential to the target ofthe content may be more effective in advertising a product. By includingthe group of transitional windows that each include separate brandmessages, each of which may further include the above-described media oruser-generated content, a content provider may increase theeffectiveness of its targeted messages by increasing the amount andvariety of the content within the content provider's targeted messageswithout necessarily crowding the graphical user interface with largermessage windows. Further, in a large scale social media environment thatrequires real-time communication, distribution, and analysis, thetechniques described herein more adequately utilize computing resourcesby enabling multiplicatively more information to be transferred betweendevices in the same message. By developing a machine learning model thatnarrows down the universe of messages on the social media platform tomessages that meet a particular interest score, the computing devicesaves processing time and reduces the amount of inputs required togather this information, as opposed to what could be a huge or nearlyinfinite number of manual queries that, due to the time it would take toprocess each query and analyze the results, would be outdated before theresults are even ascertained.

The details of one or more examples of the disclosure are set forth inthe accompanying drawings and the description below. Other features,objects, and advantages of the disclosure will be apparent from thedescription and drawings, and from the claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a conceptual diagram illustrating an example system includinga computing device that is configured to create and output, for displayat one or more client devices, targeted content that includes a carouselportion, in accordance with one or more aspects of the presentdisclosure.

FIG. 2 is a block diagram illustrating further details of an example acomputing device that is configured to create and output, for display atone or more client devices, targeted content that includes a carouselportion, in accordance with one or more aspects of the presentdisclosure.

FIGS. 3A-3B are conceptual diagrams of example targeted messages thatinclude respective carousel portions to be displayed at one or moreclient devices, in accordance with one or more techniques of thedisclosure.

FIGS. 4A-4B are conceptual diagrams of example message streams thatinclude targeted messages that include respective carousel portions tobe displayed at one or more client devices, in accordance with one ormore techniques of the disclosure.

FIG. 5 is a flow diagram illustrating example operations of a computingdevice that implements techniques to create and output, for display atone or more client devices, targeted content that includes a carouselportion, in accordance with one or more aspects of the presentdisclosure.

DETAILED DESCRIPTION

Techniques of the disclosure are directed to a computing device creatingand outputting, for display at client devices, targeted content thatincludes a carousel portion having transitional windows that eachcontain user-generated content. Such targeted content may provide usersof the client devices with a compact yet detailed message that includesboth content formed at the computing device and a series ofuser-generated content referencing a particular product, brand, ormarket. In creating this targeted content, the computing device mayreceive candidate messages composed by one or more users of a group ofclient devices, where the candidate messages each include a reference tothe requisite particular product, brand, or market. If a candidatemessage has a determined interest score that satisfies a thresholdinterest score, the computing device includes the candidate message intoa group of one or more brand messages. The computing device may thensend the targeted message to be output for display at another group ofclient devices, where the targeted message includes both an originalportion and a carousel portion. The original portion may include contentformed at the computing device itself. The carousel portion includes agroup of one or more transitional windows, where each transitionalwindow includes one of the brand messages from the group of one or morebrand messages that each reference the particular product, brand, ormarket. The transitional windows, when displayed, are cycledhorizontally within the targeted message, providing a visual contrast tothe messages within the message stream, which typically scrollvertically. In some examples, the original portion may be static whilethe carousel portion is transitionally displayed. In other examples, thecarousel portion includes the original portion, and all parts of thetargeted message are transitionally displayed.

Many social networking applications provide a limited amount of space ina graphical user interface for any message, including targeted content,to be displayed. By creating a targeted message that includes both anoriginal portion and a carousel portion, rather than limiting a creatorto only a single message, a content provider, such as an advertiser, mayinclude multiple forms of content, including organic content and usergenerated content, within a single targeted message. In some instances,media may be more effective in conveying information regarding aproduct. In other instances, user-generated content created by a partyinfluential to the target of the content may be more effective inadvertising a product. By including the group of transitional windowsthat each include separate brand messages, each of which may furtherinclude media, a content provider may increase the effectiveness of itstargeted messages by increasing the amount and variety of the contentwithin the content provider's targeted messages without necessarilycrowding the graphical user interface with larger message windows.Further, in a large scale social media environment that requiresreal-time communication, distribution, and analysis, the techniquesdescribed herein more adequately utilize computing resources by enablingmultiplicatively more information to be transferred between devices inthe same message. By developing a machine learning model that narrowsdown the universe of messages on the social media platform to messagesdealing only with a common category of entities, the computing devicesaves processing time and reduces the amount of inputs required togather this information, as opposed to what could be a huge or nearlyinfinite number of manual queries that, due to the time it would take toprocess each query and analyze the results, would be outdated before theresults are even ascertained.

FIG. 1 is a conceptual diagram illustrating a system 100 including acomputing device 120 that is configured to create and output, fordisplay at client devices, targeted content that includes a carouselportion, in accordance with one or more aspects of the presentdisclosure. System 100 includes client device 101A, client device 102A,information distribution system 112, computing device 120, and network128.

Network 128 represents any communication network (e.g., public, private,commercial, governmental, or residential) that communicatively links twoor more computing devices or systems for the transmission ofinformation. For example, network 128 may be a wireless and/or wirednetwork for transmitting data between two or more computing deviceslocated at two or more different physical locations. In some examples,network 128 may represent the Internet. Client device 102A, informationdistribution system 112, and computing device 120 may send and receivedata via network 128 using various suitable communication techniques.For instance, data may be transmitted between the devices usingcommunication links 135A-135D, which may be wired and/or wireless links.Network 128 may include any required hardware for communicativelylinking computing client device 102A, client device 101A, informationdistribution system 112, and computing device 120. For example, network128 may include various switches, hubs, routers, and other networkequipment that provides for the exchange of information between thedevices.

Client device 101A and 102A each represent any type of personalcomputing device from which a person can view, listen to, feel, orotherwise obtain output based at least in part on information receivedvia a network, such as network 128. For example, client device 101A orclient device 102A may be a laptop computer, a mobile telephone, atablet computer, a set-top box, a desktop computer, a server, amainframe, a wearable device (e.g., a watch, computerized glasses, andthe like), a personal digital assistant (PDA), a gaming system, a mediaplayer, an e-book reader, a television platform, a digital media player,an automobile navigation and/or entertainment system, or any other typeof mobile and/or non-mobile computing device that is configured tocommunicate (e.g., transmit and receive data) across a network andoutput information received via the network to a user. Although notshown in FIG. 1, client device 101A may include similar components asclient device 102A that perform similar functions.

Client device 102A includes user interface component 104A. Userinterface component 104A may include various technologies for receivinginput from, and/or outputting information to, a user of user device102A. For example, user interface component 104A may include amicrophone, a touch screen or other type of presence-sensitive screen,and other types of sensors and input devices for receiving input from auser. User interface component 104A may include a display (e.g., liquidcrystal (LCD), light emitting diode (LED), organic light-emitting diode(OLED), or any other type of display), a speaker, a haptic feedbackdevice, or any other type of output device for outputting visible,audible, and/or haptic feedback type information to a user of clientdevice 104A. Although illustrated as a presence-sensitive displayintegrated with client device 102A, in some examples, user interfacecomponent 104A may be a display device, such as a monitor integrated ina laptop computer, or a standalone monitor coupled to a desktopcomputing device, to name only a few examples.

User interface component 104A may provide a user interface from which auser may interact with client device 102A to cause client device 104A toperform one or more operations. For example, user interface component104A may give a user access to a service, provided by informationdistribution system 112, for receiving content (e.g., social media,news, television, streaming audio, streaming video, or other types ofcontent) distributed across network 128. As further described in thisdisclosure, information distribution system 112 may provide content vianetwork 128 to client device 102A. Client device 102A may process andoutput the content as one or more graphical images, sounds, andhaptic-feedback sensations, at user interface component 104A.

Client device 102A may include a client module 106A. Client module 106Amay send information generated by a user to and receive information froman information network provided by information distribution system 112.For instance, a user may have a user account stored at informationdistribution system 112. The user account may include a uniqueidentifier (e.g., a username) for the user, authentication credentials,and personal information (e.g., name, phone number, email address, homeaddress, to name only a few examples). Client module 106A mayauthenticate with information distribution system 112 based at least inpart on authentication credentials provided by the user to client device102A.

In some examples, client module 106A may provide a graphical userinterface (GUI) that enables a user to generate or otherwise composeuser content that client module 106A sends to information distributionsystem 112. Such user content may include text, images, video, and/oraudio information. In some examples, a user may compose a message thatincludes various content. In addition to content, a message may includeone or more hashtags and/or mention tags. In some examples, a hashtagmay represent or otherwise identify a particular topic associated withthe content of a message. As such, a user composing a message on aparticular topic may associate hashtag for the topic with the message. Amention tag may represent or otherwise identify a particular user thathas a corresponding user account at information distribution system 112.A user composing a message who wishes to refer to or address anotherparticular user may associate a mention tag for the particular user withthe message. When a user generates user content, client module 106A maysend user content to information distribution system 112, which mayprocess and/or distribute the user content as further described in thisdisclosure.

Similar messages may be composed using client device 101A. In someexamples, a user of client device 101A may compose a message thatincludes various content. In addition to content, a message may includeone or more hashtags and/or mention tags. In some examples, a hashtagmay represent or otherwise identify a particular topic associated withthe content of a message. As such, a user composing a message on aparticular topic may associate hashtag for the topic with the message. Amention tag may represent or otherwise identify a particular user thathas a corresponding user account at information distribution system 112.A user composing a message who wishes to refer to or address anotherparticular user may associate a mention tag for the particular user withthe message. When a user generates user content 108, client device 101Amay send user content to information distribution system 112, which mayprocess and/or distribute user content 108 as further described in thisdisclosure.

Client module 106A may enable the user to perform one or more functionsassociated with user content. For instance, client module 106A mayenable a user to “share,” “re-share,” “read,” and “follow” content aswell as “follow” and “mention” other users. In some examples, “sharing”a message or content may refer to composing an original message ororiginal content that is subsequently distributed by informationdistribution system 112 to other users. In some examples, “re-sharing” amessage or content may refer to an operation initiated by a user tore-post a message or content that was originally generated by anotheruser. In some examples, “reading” a message or content may refer to anactivity of a user to view the message or content. In some examples,“following” may refer to an operation initiated by a user to subscribeto messages and/or user content of another user. As such, a user thatfollows a particular user may receive updates of messages and/or usercontent generated by the particular user. In some examples, “mentioning”a particular user may refer to an operation initiated by a user toidentify or otherwise associate the particular user with a message oruser content.

Client module 106A may perform operations described herein usingsoftware, hardware, firmware, or a mixture of both hardware, software,and firmware residing in and executing by client device 102A or at oneor more other remote computing devices. As such, client module 106A maybe implemented as hardware, software, and/or a combination of hardwareand software. Client device 102A may execute client module 106A as orwithin a virtual machine executing on underlying hardware. Client module106A may be implemented in various ways. For example, client module 106Amay be implemented as a downloadable or pre-installed application or“app.” In another example, client module 106A may be implemented as partof an operating system of client device 102A.

As shown in FIG. 1, system 100 also includes information distributionsystem 112. Information distribution system 112 may implement techniquesof this disclosure to detect trends in user-generated content based atleast in part on one or more hashtags and provide user informationregarding the authors of candidate messages to computing device 120.Information distribution system 112 may be implemented as one or morecomputing devices, including but not limited to: desktop computers,laptop computers, mainframes, servers, cloud computing systems, and thelike.

Information distribution system 112 may include data and one or moremodules, that when executed perform one or more operations. For examplepurposes, information distribution system 112 includes distributionmodule 114, user data 116, and targeted content 118; however,information distribution may include more or fewer modules or data inother examples. User data 116 may include data representing useraccounts and demographic data about each user. As described above, auser account for a user of information distribution system 112 mayinclude but is not limited to: a user name, password, phone number,email address, and home address. In some examples, user data 116 mayalso include, current location of the user, devices authenticated withthe user, interests of the user, history of content generated by theuser, history of content read and/or followed by a user, hashtags and/ormention tags used by the user, other users followed by the user, otherusers following the user, private messages sent and/or received by theuser, and/or search history of the user, to name only a few examples.

For instance, information distribution system 112 may include targetedcontent 118. Targeted content may include any targeted content createdby computing device 120 or any number of similar computing devices. Inthe instance where targeted content 118 includes targeted contentcreated by computing device 120, information distribution system 120 mayreceive targeted content 122 (i.e., targeted content created bycomputing device 120) from computing device 120 and store the receivedtargeted content 122 in targeted content 118.

Information distribution system 112 may also include distribution module114. Distribution module 114 may construct and maintain informationgenerated by users and/or operators of information distribution system112. Distribution module 114 may receive user content 108 from one orclient devices, and store and organize the user content in theinformation network. The user content may be stored and organized usingany number of datastores and data structures, such as but not limited tographs, lists, tables, a Relational Database Management System (RDBMS),Object Database Management System (ODBMS), and/or Online AnalyticalProcessing (OLAP) system.

Distribution module 114 may parse or analyze user content to share orotherwise redistribute the user content to other users of informationdistribution system 112. For example, numerous users may each share orre-share content for a particular topic, and include or associatehashtag for the topic with the content. As an example, multiple usersmay each share content about the Olympics and include a hashtag#Olympics with the content (e.g., text and/or pictures). Distributionmodule 114 may receive the content and parse the hashtag #Olympics tostructure content associated with the hashtag as searchable. In thisway, if a user wishes to view all content associated with #Olympics, theuser may submit a query to distribution module 114, which may return aset of content or messages that include the hashtag #Olympics. In someexamples, distribution module 114 may automatically send to a user'sclient device, without additional user intervention, content or messagesthat include the hashtag #Olympics, if the user previously searched for,shared, re-shared, and/or viewed content associated with the hashtag#Olympics.

Distribution module 114 may parse or analyze user content to share orotherwise redistribute the user content to other users of informationdistribution system 112 based at least in part on whether a user isfollowing another particular user or has mentioned the particular user.For instance, if the user provides user input to client module 106A tofollow a particular user, information distribution system 112 mayreceive an indication of the user input and store the indication withthe user's account. When the particular user shares or re-sharescontent, information distribution system 112 may send the content toclient device 102A such that the user can view the content. As anotherexample, if the user mentions the particular user in shared or re-sharedcontent, information distribution system 112 may receive the content andsend the content or notification of the mention to a client device ofthe particular user that was mentioned. In some examples, distributionmodule 114 may store information about user content viewed by aparticular user. For instance, client module 106A may send data thatindicates the user has viewed specific user content to informationdistribution system 112. Distribution module 114 may store data thatindicates the user has viewed the specific user content. Although anumber of examples above have described how distribution module 114determines relationships between user content and redistributes usercontent to client devices, many other examples of distributing contentand determining relationships are also possible.

In some instances, the amount of content associated with a particularhashtag may grow or decline rapidly relative to content associated withother hashtags. The rapid change may be due to a particular event,controversy, person, or topic that captures or loses the interest of alarge audience of users. Such change in the increase or decrease ofcontent associated with the hashtag may represent a trend. A magnitudeof a trend may represent the degree interest or engagement by anaudience of users. For instance, if a magnitude of a trend is high, thedegree of interest by the audience of users may be high. As an example,there may be relatively more users in the audience and those users maybe more engaged in content for the particular event, controversy,person, or topic. Conversely, if a magnitude of a trend is low, thedegree of interest by the audience of users may be low. As an example,there may be relatively fewer users in the audience and those users maybe less engaged in content for the particular event, controversy,person, or topic.

In some examples, distribution module 114 may, in addition tore-distributing user content to client devices as described above, sendtargeted content to client devices for display. Targeted content mayinclude, but is not limited to: advertisements, offers, rewards,discounts, political information, public interest information,entertainment information, sports information, or any otherinformational content. As shown in FIG. 1, distribution module 112 maysend collocated content 110 that includes targeted content and/ordistributed user content from other users. Client module 106A maygenerate a graphical user interface 130 for display that includesinformation included in collocated content 110, such as user content 134and targeted message 136. In some examples, user interface 130 outputsinformation in a sequence or stream of “cards” or graphical userelements 132A-132D (hereinafter, “cards 132”). The sequence or stream of“cards” may be ordered in chronological or reverse chronological order,in some examples. As shown in FIG. 1, card 132B includes an icon 138Aand user content 134. Card 132C includes an icon 138B and targetedmessage 136. Icon 138A may correspond to the particular user that sharedor re-shared user content 134. Icon 138B may correspond to theparticular content provider that provided targeted message 136.

As shown in FIG. 1, targeted message 136 may be interspersed with otheruser content in graphical user interface 130. Accordingly, if a user isviewing a sequence or stream of cards, such as cards 132, informationdistribution system 112 may also include one or more cards with targetedcontent. As an example, if the sequence or stream of cards is associatedwith a specific topic, targeted content that is relevant to the specifictopic may be included in the sequence or stream of cards.

As shown in FIG. 1, system 100 also includes computing device 120.Computing device 120 may implement techniques of this disclosure tocreate and output, for display at client device 102A, targeted contentthat includes a carousel portion. Computing device 120 may beimplemented as one or more computing devices, including but not limitedto: desktop computers, laptop computers, mainframes, servers, cloudcomputing systems, and the like.

In some examples, information distribution system 112 may receivetargeted content from content providers operating one or more contentprovider systems, such as computing device 120. Content providers mayinclude advertising agencies, companies, public interest organizations,governments, individual persons, and political candidates, to name onlya few examples. Such content providers may be interested in providingtarget content to users of information distribution system 112. Moreparticularly, content providers may be interested in generating anddisplaying targeted content to specific audiences (e.g., sets of usersof information distribution system 112) that are highly engaged orinterested in a particular event, controversy, person, or topic.

Computing device 120 may include data and one or more modules, which,when executed, perform one or more operations in accordance with thetechniques of this disclosure. For example purposes, computing device120 includes interest module 124 and targeted content 126; however,computing device 120 may include more or fewer modules or data in otherexamples. Targeted content 126 may include data representing useraccounts, demographic data about each user, user-generated contentregarding a particular product, brand, or product market, and interestscores that represent a likelihood that a user of client device 102Awould interact with an instance of targeted content 126 if it included aparticular brand message.

Computing device 120 may also include interest module 124. Interestmodule 124 may construct and maintain information generated by usersand/or operators of computing device 120. Interest module 124 mayreceive user content 108 from information distribution system 112, andstore and organize the user content within computing device 120 attargeted content 126. The user content may be stored and organized usingany number of datastores and data structures, such as but not limited tographs, lists, tables, a Relational Database Management System (RDBMS),Object Database Management System (ODBMS), and/or Online AnalyticalProcessing (OLAP) system.

Each of the messages received by interest module 124 of computing device120 may be composed by one or more users of the one or more clientdevices accessing a social media platform on information distributionsystem 112. Further, each of the messages may include a reference to aparticular brand. For instance, in the example of FIG. 1, the particularbrand may be for a particular candy. As such, each of the messages mayinclude a reference to the brand of the particular candy. For instance,a message may include any words describing the particular brand, theparticular candy, or any other market identifier that one wouldordinarily associate with the particular brand or candy, such as aslogan for the candy or a trademarked word or phrase. In some examples,information distribution system 112 may only send messages to computingdevice 120 that include the references to the particular brand. In otherinstances, information distribution system 112 may send a larger groupof messages to computing device 120. In such instances, interest module124 of computing device 120 may pare down the received group of messagesby disregarding any messages that do not include reference to theparticular brand.

The first group of one or more messages received by interest module 124may include a candidate message. Interest module 124 may determine aninterest score for the candidate message using a machine learning model,the interest score being based at least in part on content of thecandidate message. In some instances, the interest score may be specificto a user of a client device that will receive a targeted message. Inother instances, the interest score may be generally applicable to agroup of client devices or all client devices. In general, the interestscore represents a likelihood that a user would interact with a targetedmessage if the targeted message included the candidate message as partof the targeted message's content. For instance, if the candidatemessage was drafted by a user of a social networking platform that isnot influential (e.g., the user does not have a large number ofsubscribers to their social media account), or the content of thecandidate message includes multiple grammatical errors, then interestmodule 124 may determine that the interest score for the candidatemessage is low. Conversely, if the candidate message was drafted by auser of a social networking platform that is very influential (e.g., theuser has millions of subscribers to their social media account, like acelebrity) and the content of the candidate message is creative,well-crafted, and grammatically sound, then interest module 124 maydetermine that the interest score is very high.

In the example scenario of FIG. 1, a celebrity with a large amount ofsubscribers to their social media account may generate a candidatemessage that includes a creative and favorable reference to theparticular brand of candy. The candidate message may also include media,such as audio, a video, a picture (e.g., a joint photographic group(JPG) file, a joint photographic expert group (JPEG) file, a taggedimage file format (TIFF) file, a portable network graphics (PNG) file,etc.), or an animated image file (e.g., a graphics interchange format(GIF) file, an animated PNG (APNG) file, a multiple-image networkgraphics (MNG) file, a scalable vector graphics (SVG) file. etc.). Basedon this information, interest module 124 may determine that thecandidate message has a high interest score that satisfies a thresholdinterest score. Responsive to this determination, interest module 124may insert the candidate message into a group of one or more brandmessages. Each brand message in the group of one or more brand messagesincludes a reference to the particular brand. In other words, each ofthe brand messages is a candidate message that references the particularbrand and has an interest score that satisfies the previously referencedthreshold interest score.

Interest module 124 may send, to information distribution system 112, atargeted message to be output for display at client device 102A. Thetargeted message may include an original portion and a carousel portion.The original portion may merely include content formed at computingdevice 120. The carousel portion may include a group of one or moretransitional windows, where each transitional window in the group of oneor more transitional windows includes one of the brand messages in thegroup of one or more brand messages. Each of the one or moretransitional windows contain user-generated content, enabling clientdevice 102A to show multiple user-generated endorsements of and/or mediadescribing a specific product or brand. Such targeted content mayprovide users of client device 102A with a compact yet detailed messagethat includes both content formed at computing device 120 and a seriesof user-generated content referencing a particular product, brand, ormarket. An illustration of an example targeted message is shown infurther detail with respect to FIGS. 3A and 3B.

In the example of FIG. 1, interest module 124 may send a targetedmessage to information distribution system 112. The original portion ofthe targeted message may include content generated by a user ofcomputing device 120 describing the particular brand of candy. Interestmodule 124 may further include multiple transitional windows in thetargeted message. One such transitional window may include the candidatemessage drafted by the celebrity with a large amount of subscribers totheir social media account. Other transitional windows may include otherbrand messages that satisfy the threshold interest score. Client device102A may output the targeted message such that the original portion ofthe targeted message is static in the graphical user interface. Clientdevice 102A may output the carousel portion such that a singletransitional window is fully visible, but also such that client device102A may transition between the transitional windows dynamically, eitherautomatically after a certain amount of time or in response to receivingan indication of user input. This allows multiple additional pieces ofcontent to be present in a single message without excessively wastingarea on the graphical user interface at client device 102A. By includingthe group of transitional windows that each include separate brandmessages, each of which may further include media, computing device 120may increase the effectiveness of targeted messages by increasing theamount and variety of the content within the content provider's targetedmessages without necessarily crowding the graphical user interface withlarger message windows.

As shown in FIG. 1, each of cards 132 is displayed such that a verticaltransition occurs on UI component 104A when scrolling between cards 132.However, targeted message 136, which includes the carousel portions, isdisplayed such that a horizontal transition occurs on UI component 104Awhen scrolling between transitional windows of the group of one or moretransitional windows. This creates a distinguishing visual effect thatmakes targeted message 136 easier to interact with and places targetedmessage 136 in a more noticeable position within the message streamdisplayed in user interface 130.

FIG. 2 is a block diagram illustrating further details of an example acomputing device that is configured to create and output, for display atclient devices, targeted content that includes a carousel portion, inaccordance with one or more aspects of the present disclosure. Computingdevice 120 of FIG. 2 is described below within the context of FIG. 1.FIG. 2 illustrates only one particular example of computing device 120,and many other examples of computing device 120 may be used in otherinstances and may include a subset of the components included in examplecomputing device 120 or may include additional components not shown inFIG. 1.

As shown in the example of FIG. 2, computing device 120 includes messageassembly module 220, interest module 124, targeted content 126,secondary information 230, credit account 232, machine learning model234, operating system 202, one or more storage devices 204, one or moreinput devices 206, one or more communication units 208, one or moreoutput devices 210, one or more processors 212, and one or morecommunication channels 226.

Communication channels 226 may interconnect each of the components202-234 for inter-component communications (physically, communicatively,and/or operatively). In some examples, communication channels 226 mayinclude a system bus, a network connection, an inter-processcommunication data structure, or any other method for communicatingdata.

One or more input devices 206 of computing device 120 may receive inputand one or more output devices 210 may generate output. Examples ofinput are tactile, audio, and video input and examples of output aretactile, audio, and video output. In one example, input devices 206include a presence-sensitive display, touch-sensitive screen, mouse,keyboard, voice responsive system, video camera, microphone, or anyother type of device for detecting input from a human or machine.Whereas in one example, output devices 210 include a presence-sensitivedisplay, sound card, video graphics adapter card, speaker, cathode raytube (CRT) monitor, liquid crystal display (LCD), or any other type ofdevice for generating output to a human or machine.

One or more communication units 208 may allow computing device 120 tocommunicate, via one or more wired and/or wireless networks, withexternal devices and/or systems, such as information distribution system112. For example, communication units 208 may transmit and/or receivenetwork signals being transmitted and received other devices and/orsystems connected to network 128. Examples of communication units 208include network interface cards (e.g. such as an Ethernet card), opticaltransceivers, radio frequency transceivers, GPS receivers, or any othertype of device that can send and/or receive information via a network.Other examples of communication units 208 may include long and shortwave radios, cellular data radios, wireless network radios, as well asuniversal serial bus (USB) controllers.

One or more storage devices 204 of computing device 120 may storeinformation or instructions that computing device 120 processes duringoperation of computing device 120. For example, storage devices 204 maystore data that modules or components may access during execution atcomputing device 120. In some examples, storage devices 204 aretemporary memories, meaning that a primary purpose of storage devices204 is not long-term storage.

Storage devices 204 may be configured for short-term storage ofinformation as volatile memory and therefore not retain stored contentsif powered off. Examples of volatile memories include random accessmemories (RAM), dynamic random access memories (DRAM), static randomaccess memories (SRAM), and other forms of volatile memories known inthe art.

Storage devices 204 may be configured to store larger amounts ofinformation than volatile memory and may further be configured forlong-term storage of information as non-volatile memory space and retaininformation after power on/off cycles. Examples of non-volatile memoriesinclude magnetic hard discs, optical discs, floppy discs, flashmemories, or forms of electrically programmable memories (EPROM) orelectrically erasable and programmable (EEPROM) memories.

Storage devices 204, in some examples, include one or morecomputer-readable storage media. In some examples, storage devices 204represent non-transitory computer readable storage medium that storeinstructions later executed by one or more processors 212 duringoperation of computing device 120. For example, storage devices 204 maystore program instructions and/or information (e.g., data) associatedwith modules and/or components 124, 126, 220, 230, 232, 234, and 202.

One or more processors 212 may implement functionality and/or executeinstructions within computing device 120. For example, processors 212 oncomputing device 120 may receive and execute instructions stored bystorage devices 204 that execute the functionality of modules 124, 126,220, 230, 232, 234, and 202. The instructions executed by processors 212may cause computing device 120 to read/write/etc. information, such asone or more data files at targeted content 126 and/or secondaryinformation 230 and/or credit account 232 and/or machine learning model234 and stored within storage devices 204 during program execution.Processors 212 may execute instructions of modules 124, 220, and 202 tocause computing device 120 to perform the operations described in thisdisclosure. That is, modules 124, 220, and 202 may be operable byprocessors 212 to perform various actions or functions of computingdevice 120, for instance, generating and dispersing targeted contentthat includes an original portion and a carousel portion, in accordancewith one or more aspects of the present disclosure.

Interest module 124 may receive user content 108 from informationdistribution system 112, and store and organize the user content withincomputing device 120 at targeted content 126. Targeted content 126 maybe stored and organized using any number of datastores and datastructures, such as but not limited to graphs, lists, tables, aRelational Database Management System (RDBMS), Object DatabaseManagement System (ODBMS), and/or Online Analytical Processing (OLAP)system.

Each of the messages received by interest module 124 of computing device120 may be composed by one or more users of the one or more clientdevices accessing a social media platform. Further, each of the messagesmay include a reference to a particular brand. For instance, in theexample of FIG. 2, the particular brand may be for a particularbasketball shoe. As such, each of the messages may include a referenceto the brand of the particular basketball shoe. For instance, a messagemay include any words describing the particular brand, the particularshoe itself, or any other market identifier that one would ordinarilyassociate with the particular brand or shoe, such as a slogan for theshoe or a trademarked word or phrase. In some examples, informationdistribution system 112 may only send messages to computing device 120that include the references to the particular brand. In other instances,information distribution system 112 may send a larger group of messagesto computing device 120. In such instances, interest module 124 ofcomputing device 120 may pare down the received group of messages bydisregarding any messages that do not include reference to theparticular brand.

The first group of one or more messages received by interest module 124may include a candidate message. Interest module 124 may determine,using machine learning module 234, an interest score for the candidatemessage based at least in part on content of the candidate message. Insome instances, the interest score may be specific to a user of a clientdevice that will receive a targeted message. In other instances, theinterest score may be generally applicable to a group of client devicesor all client devices. In general, the interest score represents alikelihood that a user would interact with a targeted message if thetargeted message included the candidate message as part of the targetedmessage's content. For instance, if the candidate message was drafted bya user of a social networking platform that is not influential (e.g.,the user does not have a large number of subscribers to their socialmedia account), or the content of the candidate message includesmultiple grammatical errors, then interest module 124 may determine thatthe interest score for the candidate message is low. Conversely, if thecandidate message was drafted by a user of a social networking platformthat is very influential (e.g., the user has millions of subscribers totheir social media account, like a celebrity) and the content of thecandidate message is creative, well-crafted, and grammatically sound,then interest module 124 may determine that the interest score is veryhigh.

In general, the interest score may be indicative of a strength of arelation between the content of the candidate message and a particularproduct belonging to the particular brand. In other words, if thecontent of the candidate message closely describes or directlyreferences a product of the particular brand or the particular brand ingeneral, interest module 124 may determine a relatively higher interestscore for the candidate message. Conversely, if the content of thecandidate message does not reference the particular brand or looselyreferences the market to which the particular brand belongs, theninterest module 124 may determine a relatively lower interest score.

In some examples, interest module 124 may incorporate secondaryinformation stored in secondary information 230 when determining theinterest score. For instance, secondary information for the candidatemessage may include an author of the candidate message (e.g., includingthe market power of the author), a number of subscribers to a socialmedia account of the author of the candidate message, a probability thata user of a client device of the second group of one or more clientdevices will engage with the candidate message, an interaction historybetween the user of the client device of the second group of one or moreclient devices and the author of the candidate message, a time that thecandidate message was authored, a geolocation of a client device of thefirst group of one or more client devices used by the author of thecandidate message to post the candidate message, or a topic of thecandidate message. Interest module 124 may utilize the secondaryinformation to determine the interest score for the candidate message.

For instance, if the candidate message is authored by a famous user witha large number of subscribers, was authored by a user with similarinterests to the targeted user, was authored by a user who the targeteduser has interacted with in the past, was composed recently, wascomposed at a geographical location close to a geolocation of thetargeted user, or is regarding a topic of interest to the targeted user,to list only a few non-limiting examples, interest module 124 mayincrease the interest score for the candidate message. Conversely, ifthe candidate message is authored by a pedestrian user with a smallnumber of subscribers, was authored by a user with different intereststhan the targeted user, was authored by a user who the targeted user hasnever interacted with in the past, was composed multiple years prior tothe current date, was composed at a geographical location far away froma geolocation of the targeted user, or is regarding a topic that doesnot interest the targeted user, interest module 124 may, in theseexamples, decrease the interest score for the candidate message. In someinstances, a user of computing device 120 may further mark particularmessages for being included in the set of brand messages or removeparticular messages from being included in the set of brand messages.

Machine learning techniques may include any techniques that enableinterest module 124 to update machine learning model 234 and itsvocabulary to more accurately and more efficiently identify messagesthat reference a particular product market, a particular brand withinthe product market, or a particular product for the brand, and todetermine an interest score for the messages determined to referencesaid products or brands. For instance, interest module 124 may utilizeone or more of decision tree learning, association rule learning,artificial neural networks, deep learning, inductive logic programming,support vector machines, clustering, Bayesian networks, reinforcementlearning, representation learning, similarity and metric learning,sparse dictionary learning, and/or rule-based machine learning inimplementing machine learning techniques and machine learning model 234.Interest module 124 may utilize machine learning techniques to analyzemessages and separate messages into the correct product market anddetermining interest scores for the particular message, especially whenbrands and/or products have names that are exceptionally similar (e.g.,the difference between a fruit and a technology company).

Machine learning model 234 may further be updated to alter how theinterest score itself is determined. For instance, based on messagesthat receive user interactions, interest module 124 may update machinelearning model 234 to better predict the types of accounts that wouldinfluence the user to be more likely to interact with the targetedmessage or less likely to interact with the targeted message, such thatthe targeted message includes brand messages that the user is morelikely to interact with. Interest module 124 may further update machinelearning model 234 to better predict the type of language or the type ofproducts that the user is more likely to interact with.

Additionally, when the targeted message is created based on a selectedtrend, interest module 124 may be configured to update machine learningmodel 234 to determine which accounts associated with that trend mayhave an influence on the user, including optimal positions for originalcontent to be placed within the carousel portion of the trend such thatthe user is most likely to interact with the original content for abrand associated with the selected trend.

One example machine learning model 234 that interest module 124 mayleverage includes a neural network system. Neural networks are machinelearning models that employ one or more layers of nonlinear units topredict an output for a received input. Some neural networks include oneor more hidden layers in addition to an output layer. The output of eachhidden layer is used as input to the next layer in the network, i.e.,the next hidden layer or the output layer. Each layer of the networkgenerates an output from a received input in accordance with currentvalues of a respective set of parameters.

A neural network system may receive multiple input feature values andprocess the input feature values to generate one or more networkoutputs. Each input feature value may describe a particular feature ofan input data item, and each network output may describe a computedproperty of the input data item. For example, an input feature value maydescribe a common product market, or a particular brand and/or product.As another example, an input feature value may describe a feature, e.g.,a count of likes, a count of shares, a count of occurrence of aparticular word or phrase, and so on, of a social media posting, e.g., atweet, and a network output may describe a predicted user interest for aparticular user in the social media posting. Each input feature valuebelongs to an input feature value type and has a raw value. An inputfeature value type indicates the feature of the input data item that thecorresponding input feature value describes. The raw value in an inputfeature value is a value assigned to the input feature value type.

The neural network system may include a discretization layer, a sparsecalibration layer, and one or more additional layers. The discretizationlayer determines a total range of values for each input feature valuetype and discretizes these features prior to being fed into the maindeep neural network. A total range of values for an input feature valuetype includes a minimum value and a maximum value for the input featurevalue type. The discretization layer can determine a minimum and amaximum value of input feature values belonging to an input featurevalue type in a collection of input training data as the minimum valueand the maximum value for the input feature value type respectively. Thediscretization layer can also use a predetermined minimum value andmaximum value for the input feature values belonging to a particularinput feature value type as the minimum value and the maximum value forthe particular input feature value type respectively. The discretizationlayer divides, for each input feature value type, the total range ofvalues for the input feature value type into multiple bins, e.g.,multiple bins that each include an equal range of possible values. Eachbin includes a range of possible values in the total range of values forthe input feature value type.

By converting an input feature value to multiple discretized featurevalues that each has a significant variance in value, the neural networksystem can increase the significance of the feature values used by theadditional layers to make inferences and generate multiple useful piecesof information from the input feature value. By doing this, the neuralnetwork system can increase the accuracy of inferences made by theadditional layers. This technique is especially useful for processingcollections of input feature values that are generally sparse, e.g.,generally include mostly zero or low values.

A sparse calibration layer of the neural network system obtains thediscretized feature values and generates refined feature values bynormalizing the discretized feature values to generate normalizedfeature values and applying a type-specific bias value to eachnormalized feature value. This layer has two main extras compared toother sparse layers out there, namely an online normalization schemethat prevents gradients from exploding, and a per-feature bias todistinguish between the absence of a feature and the presence of azero-valued feature. The sparse calibration layer can normalize adiscretized feature value by dividing a value associated with adiscretized value type of the discretized feature value by a maximumvalue for the input feature value type that corresponds to an inputfeature value using which the discretized feature value is generated.The sparse calibration layer also applies, e.g., adds, a type-specificbias value to each normalized feature value. A type-specific bias valueis associated with a particular input feature value type and is commonto all normalized feature values that are generated using input featurevalues belonging to the particular input feature value type.

Another layer of the neural network system may include a sampling schemelayer associated with a calibration layer. Stacked neural networksusually explore the space of solutions much better when the trainingdataset contains a similar number of positive and negative examples.However, hand-tuning a training dataset in this manner may lead touncalibrated output predictions. Thus, a custom isotonic calibrationlayer may recalibrate and output actual probabilities.

The additional layers of the neural network system may include one ormore other neural network layers, such as one or more feedforwardfully-connected layers, one or more feedforward convolutional layers,one or more recurrent layers, one or more testing layers, one or moresoftmax layers, one or more calibration layers, and the likes. Theadditional layers process the refined feature values to generate thenetwork outputs.

A training engine can train the sparse calibration layer and theadditional layers using any neural network training algorithm, such as atraining algorithm that relies on backpropagation with gradient descent.The training engine can use observed data, such as observed data aboutuser engagement and/or interest in a social media posting through likes,re-sharings, and so on, as the target output data for training.

Machine learning models that include, or wholly comprise, neuralnetworks may be specifically suited for use in large-scale social mediaplatforms with heavy latency. Neural networks may provide the machinelearning capability to update dictionaries and contexts for commonproduct markets, specific brands, and specific products, while operatingin an environment that requires low latency and high accuracy in orderto provide at least a satisfactory user experience.

Deep learning models, such as the stacked neural network systemdescribed above, are models that are intrinsically modular. Deeplearning modules may be composed in various ways (stacked, concatenated,etc.) to form a computational graph. The parameters of this graph maythen be learned, such as by using back-propagation and stochasticgradient descent on mini-batches.

Low-level modules used by deep learning models that may be any hardwareor software module configured to compute the output from input andnecessary gradients. Some such modules may perform basic operations onchunks of data, potentially letting the user specify the algorithm inits preferred tensor manipulation package, and trusting the library togenerate the computational graph itself. In other examples, thecomputational graph may be dynamic and change from one mini-batch to theother. Deep learning techniques may also be scalable, as these modelslearn from mini-batches of data, the total dataset size can bearbitrarily large.

Interest module 124 may also utilize a user feedback system, wheremessages that are incorrectly included in the first group of one or moremessages, as indicated by users of the system, are analyzed. Interestmodule 124 may determine particular language used in the incorrectmessages to build its contextual knowledge, removing future messagesthat include similar language from consideration when determining theengagement score. Similarly, interest module 124 may receive anindications of user input to include particular messages that werepreviously excluded. In such instances, interest module 124 may analyzethe language of such messages to determine particular language used inthe correct messages to build its contextual knowledge, including futuremessages that include similar language for consideration whendetermining the engagement score.

In some instances, upon determining the interest score, interest module124 may save an indication of the interest score for the candidatemessage in machine learning model 234. Interest module 124 may referencemachine learning model 234 in future instances of determining theinterest score for the candidate message.

In the example scenario of FIG. 2, a celebrity with a large number ofsubscribers to their social media account may generate a candidatemessage that includes a creative and favorable reference to theparticular brand of basketball shoe. The candidate message may alsoinclude media, such as a picture, an animated image file, or a video.Based on this information, interest module 124 may determine that thecandidate message has a high interest score that satisfies a thresholdinterest score. Responsive to this determination, message assemblymodule 220 may insert the candidate message into a group of one or morebrand messages. Each brand message in the group of one or more brandmessages includes a reference to the particular brand. In other words,each of the brand messages is a candidate message that references theparticular brand and has an interest score that satisfies the previouslyreferenced threshold interest score.

Conversely, a user with very few subscribers to their social mediaaccount may generate a candidate message that includes a negativereference to the particular brand of basketball shoe, or a positivereference to the particular brand of basketball shoe but with numeroustypographical errors. Based on this information, interest module 124 maydetermine that the candidate message has a low interest score that doesnot satisfy the threshold interest score. Responsive to thisdetermination, message assembly module 220 may refrain from insertingthe candidate message into the group of one or more brand messages.

Message assembly module 220 may send, to information distribution system112, a targeted message to be output for display at client device 102A.The targeted message may include an original portion and a carouselportion. The original portion may merely include content formed atcomputing device 120. The carousel portion may include a group of one ormore transitional windows, where each transitional window in the groupof one or more transitional windows includes one of the brand messagesin the group of one or more brand messages. Each of the one or moretransitional windows contain user-generated content, enabling clientdevice 102A to show multiple user-generated endorsements of and/or mediadescribing a specific product or brand. Such targeted content mayprovide users of client device 102A with a compact yet detailed messagethat includes both content formed at computing device 120 and a seriesof user-generated content referencing a particular product, brand, ormarket. An illustration of an example targeted message is shown infurther detail with respect to FIGS. 3A and 3B.

For the targeted message, each transitional window of the group of oneor more transitional windows may include a distinct graphical elementthat contains a respective brand message of the group of one or morebrand messages and information identifying a user who composed therespective brand message. For instance, the candidate message describedabove (i.e., the candidate message that satisfies the threshold interestscore) may have a designated transitional window to display the contentof the candidate message and information identifying the author of thecandidate message. Each remaining transitional window may include aseparate brand message where interest module 124 determined that thebrand message satisfied the threshold interest score. The carouselportion that contains the transitional windows may be displayed withinthe targeted message such that only a single transitional window of thegroup of one or more transitional windows is fully displayed at a giventime. A client device in the second group of one or more client devicesis configured to individually and cyclically display each transitionalwindow in the group of one or more transitional windows during a periodof time, with the transitional windows being configured to scrollhorizontally across the device's display. This horizontal scrolling isin contrast to the remainder of the messages in the message streambelonging to the user, which scroll vertically. The original portion maybe displayed within the targeted message statically. The originalportion may be content created, generated, or inserted by a user ofcomputing device 120.

In some examples, the client device of the second group of one or moreclient devices that displays the targeted message may cycle through thevarious transitional windows. In some instances, the client device maycycle the carousel portion automatically after a predetermined amount oftime such that a different transitional window of the group of one ormore transitional windows is shown in a graphical user interface at theclient device. For instance, each transitional window may be displayedfor a certain time, such as three to five seconds, before cycling to adifferent transitional window.

In other instances, the client device may cycle the carousel portionresponsive to receiving an indication of user input at the client devicesuch that a different transitional window of the group of one or moretransitional windows is shown in a graphical user interface at theclient device. In other words, the user of the client device may providesome indication of user input, such as a tap or a swipe gesture, tocycle through the various transitional windows in the carousel portionof the targeted message.

In some examples, a brand message in the group of one or more brandmessages used to create the one or more transitional windows in thecarousel portion of the message may include various forms of media thatmay be displayed at the client device that receives the targetedmessage. In some instances, the media may include one of audio, a video,a picture (e.g., a joint photographic group (JPG) file, a jointphotographic expert group (JPEG) file, a tagged image file format (TIFF)file, a portable network graphics (PNG) file, etc.), or an animatedimage file (e.g., a graphics interchange format (GIF) file, an animatedPNG (APNG) file, a multiple-image network graphics (MNG) file, ascalable vector graphics (SVG) file. etc.). In the instances where themedia includes the audio, the video, or the animated image file, theclient device that outputs the targeted message for display mayautomatically play the included media file when the client devicedisplays the transitional window that includes the brand message withthe given media file.

In the example of FIG. 2, message assembly module 220 may send atargeted message to information distribution system 112. The originalportion of the targeted message may include content generated by a userof computing device 120 describing the particular brand of basketballshoe. Message assembly module 220 may further include multipletransitional windows in the targeted message. One such transitionalwindow may include the candidate message drafted by the celebrity with alarge number of subscribers to their social media account. Othertransitional windows may include other brand messages that satisfy thethreshold interest score. Client device 102A may output the targetedmessage such that the original portion of the targeted message is staticin the graphical user interface. Client device 102A may output thecarousel portion such that a single transitional window is fullyvisible, but also such that client device 102A may transition betweenthe transitional windows dynamically, either automatically after acertain amount of time or in response to receiving an indication of userinput. This allows multiple additional pieces of content to be presentin a single message without excessively wasting area on the graphicaluser interface at client device 102A. By including the group oftransitional windows that each include separate brand messages, each ofwhich may further include media, computing device 120 may increase theeffectiveness of targeted messages by increasing the amount and varietyof the content within the content provider's targeted messages withoutnecessarily crowding the graphical user interface with larger messagewindows.

In some instances, the user of the client device that receives thetargeted message may engage with the targeted message, such as viewingthe media included in the targeted message, disseminating the targetedmessage to one or more subscribers of a social media account associatedwith the targeted message, viewing the targeted message, or visiting awebpage from a hyperlink present in the targeted message, to name only afew examples. In such instances, interest module 124 may receive, frominformation distribution system 112, an indication that the user of theclient device of the second group of one or more client devices engagedwith the targeted message. In some instances, responsive to receivingthe indication that the user of the client device of the second group ofone or more client devices engaged with the targeted message, interestmodule 124 may update the data stored in machine learning model 234 toindicate that the user of the client device engaged with the targetedmessage. In doing so, interest module 124 may increase the interestscore in machine learning model 234 such that similar targeted messagesare sent to the client device in the future. Conversely, if interestmodule 124 does not receive an indication that the user engaged with thetargeted message, interest module 124 may decrease the interest score inmachine learning model 234 such that different targeted messages aresent to the client device in the future.

In some instances, credit account 232 associated with computing device120 may profit from users engaging with targeted messages. In suchinstances, responsive to receiving the indication that the user of theclient device of the second group of one or more client devices engagedwith the targeted message, credit account 232 of computing device 120may receive a credit from an account associated with informationdistribution system 112. The credit may be monetary or some other pointor note, either of monetary value or of no monetary value.

In some examples, prior to the receipt of the first group of one or moremessages, computing device 120 may initially receive an indication ofuser input from a particular client device of the second group of one ormore client devices that indicates a selection of a trend that may berelated to the particular brand. As such, each of the messages in thefirst group of one or more messages includes content associated with thetrend. As such, interest module 124 may construct the carousel portionof the targeted message by placing a distinct graphical element thatcontains a respective brand message of the group of one or more brandmessages and information identifying a user who composed the respectivebrand message into a respective transitional window of the group of oneor more transitional windows, forming an additional transitional windowthat includes the original portion of the targeted message, and addingthe additional transitional window to the group of one or moretransitional windows to form an expanded group of two or moretransitional windows. Interest module 124 may send, to the informationdistribution system, the targeted message to be output for display atthe particular client device of the second group of one or more clientdevices. The targeted message is displayed such that only a singletransitional window of the expanded group of two or more transitionalwindows is fully displayed at a given time, such that the particularclient device of the second group of one or more client devices isconfigured to individually and cyclically display each transitionalwindow in the expanded group of two or more transitional windows duringa period of time, and such that a transition between the transitionalwindows of the expanded group of two or more transitional windows is ahorizontal transition.

In other words, a user may select a trend on the social media platform,or a particular subject that a large portion of accounts on the socialmedia platform (either globally or at some granularity of locality) areincluding in messages dispersed via the social media platform at arelatively same time (e.g., within a particular time frame of oneanother). In some examples, the selected trend may have a connection toa particular brand. For instance, an athlete may be a “trend” for makinga game-winning play, and the athlete may have a contract with aparticular brand of shoe that the athlete wears during games. As such,if a user selects the trend of the athlete to view messages drafted byusers discussing the athlete, the particular brand of shoe may draft theoriginal portion of the targeted message to include information aboutthe athlete's signature shoe sold by the particular brand of shoe. Thisoriginal portion of the targeted message may be included in one of thetransitional windows, and may be visible when the user who selected thetrend scrolls through the carousel portion of transitional windows.

FIGS. 3A-3B are conceptual diagrams of targeted messages that include acarousel portion to be displayed at client devices, in accordance withone or more techniques of the disclosure. For purposes of illustrationonly, the example operations are described below within the context ofcomputing device 120, as shown in FIGS. 1 and 2.

FIG. 3A shows targeted message 136. Components of computing device 120,such as message assembly module 220, may construct targeted message 136and send it to a client device via information distribution system 112.Targeted message 136 may be displayed at the recipient client device.

Targeted message 136 may include icon 138B. Icon 138B may includeidentifying information of the author of the targeted message 136, suchas a user or social media account associated with computing device 120.Icon 138B may include one or more of a picture identifier or a textualidentifier, such as a name or a social media account handle.

Targeted message 136 includes original portion 302. Original portion 302may include content formed at computing device 120. For instance,original portion 302 may be content created, generated, or inserted by auser of computing device 120. In the instance of FIG. 3A, originalportion 302 includes text authored by the user of computing device 120.However, in other instances, original portion 302 may, instead or inaddition, include media files, such as audio, a video, a picture (e.g.,a joint photographic group (JPG) file, a joint photographic expert group(JPEG) file, a tagged image file format (TIFF) file, a portable networkgraphics (PNG) file, etc.), or an animated image file (e.g., a graphicsinterchange format (GIF) file, an animated PNG (APNG) file, amultiple-image network graphics (MNG) file, a scalable vector graphics(SVG) file. etc.).

Original portion 302 may remain static while targeted message 136 isdisplayed at the client device. In other words, while other portions oftargeted message 136 may be configured to cycle in the display, originalportion 302 may remain displayed regardless of which of transitionalwindows 304A-304C is fully displayed.

Targeted message 136 may further include a carousel portion. In theexample of FIGS. 3A and 3B, the carousel portion may include a pluralityof transitional windows 304A-304C. Each of transitional windows304A-304C may include a respective brand message, where computing device120 determines that each respective brand message has an interest scorethat satisfies a threshold interest score, as described above withrespect to FIGS. 1 and 2. Transitional windows 304A-304C may bedisplayed such that the client device that displays the targeted messagemay scroll through transitional windows 304A-304C horizontally acrossthe device's display. This horizontal scrolling is in contrast to theremainder of the messages in the message stream belonging to the user,which scroll vertically across the device's display.

The recipient client device that displays targeted message 136 may beconfigured to cycle between transitional windows 304A-304C whendisplaying targeted message 136. In some examples, only one oftransitional windows 304A-304C may be displayed at any time. In otherinstances, such as the example of FIG. 3A, only one or transitionalwindows 304A-304C may be fully displayed at one time, while one or moreremaining transitional windows are at least partially visible. Forinstance, in FIG. 3A, transitional window 304B is fully displayed, whiletransitional windows 304A and 304C are partially displayed.

Transitional window 304B may include icon 306B. Icon 306B may includeidentifying information of the author of the brand message, such as auser or social media account associated with the author. Icon 306B mayinclude one or more of a picture identifier or a textual identifier,such as a name or a social media account handle.

Transitional window 304B further includes a brand message that includestextual message 308B and media file 310B. Textual message 308B and mediafile 310B may be content formed at a computing device associated withthe user identified by icon 310B. In some other instances, the brandmessage may instead include only one of textual message 308B or mediafile 310B.

Media file 310B may be any of audio, a video, a picture, or an animatedimage file. In some examples, if media file 310B is audio, a video or ananimated image file, the client device displaying targeted message 136may automatically play media file 310B upon the client device cyclingtargeted message 136 to fully display transitional window 304B.

FIG. 3B shows the same targeted message 136 described above in FIG. 3A,but after the displaying client device has cycled the carousel portionof targeted message 136 to display transitional window 304C. In someinstances, the client device may cycle the carousel portionautomatically after a predetermined amount of time such thattransitional window 304C is shown in a graphical user interface at theclient device in place of transitional window 304B (now shown mostlyhidden on the left side of the graphical user interface). For instance,transitional window 304B may be displayed for a certain time, such asthree to five seconds, before automatically cycling to transitionalwindow 304C.

In other instances, the client device may cycle the carousel portionresponsive to receiving an indication of user input at the clientdevice, such that transitional window 304C is shown in a graphical userinterface at the client device instead of transitional window 304B. Inother words, the user of the client device may provide some indicationof user input, such as a tap or a swipe gesture, to cycle through thevarious transitional windows 304A-304C in the carousel portion oftargeted message 136.

If the client display is showing the final transitional window 304C ofthe group of transitional windows, continued scrolling may loop tosubsequently display the first transitional window 304A of the group oftransitional windows. Conversely, if the client display is showing thefirst transitional window 304A of the group of transitional windows,scrolling in the reverse direction may cause the client display tooutput the final transitional window 304C of the group of transitionalwindows.

Transitional window 304C may include icon 306C. Icon 306C may includeidentifying information of the author of the brand message, such as auser or social media account associated with the author. Icon 306C mayinclude one or more of a picture identifier or a textual identifier,such as a name or a social media account handle.

Transitional window 304C further includes a brand message that includestextual message 308C and media file 310C. Textual message 308C and mediafile 310C may be content formed at a computing device associated withthe user identified by icon 310C. In some other instances, the brandmessage may instead include only one of textual message 308C or mediafile 310C.

Media file 310C may be any of audio, a video, a picture, or an animatedimage file. In some examples, if media file 310C is audio, a video, oran animated image file, the client device displaying targeted message136 may automatically play media file 310C upon the client devicecycling targeted message 136 to fully display transitional window 304C.

FIGS. 4A-4B are conceptual diagrams of targeted messages 408A-408B thatinclude a carousel portion to be displayed at a client device based on aselected trend, in accordance with one or more techniques of thedisclosure. A trend on the social media platform may be a particularsubject that a large portion of accounts on the social media platform(either globally or at some granularity of locality) are including inmessages dispersed via the social media platform at a relatively sametime (e.g., within a particular time frame of one another). Likecarousel content curation, trend detection for triggering carouselcreation is implemented by leverage machine learning that predictstrends based on any combination of time (freshness), topicality,trustworthiness, geolocation, user preferences and past actions, as wellas any other feature that may inform about user interest.

One compelling trigger is a trending topic, or a trend, about anews-breaking event, programmatically detectable by a spike in avelocity graph of a number of messages over time. In this case, theplatform generates, in real-time and while the event is still breaking,a carousel that includes both user generated content and news publishercontent describing and commenting about the event and embeds thatcarousel into timelines of users who the platform predicts would beinterested.

In some examples, prior to the receipt of the first group of one or moremessages, computing device 120 may initially receive an indication ofuser input from a particular client device of the second group of one ormore client devices that indicates a selection of a trend that may berelated to the particular brand. As such, each of the messages in thefirst group of one or more messages includes content associated with thetrend. As such, interest module 124 may construct the carousel portionof the targeted message by placing a distinct graphical element thatcontains a respective brand message of the group of one or more brandmessages and information identifying a user who composed the respectivebrand message into a respective transitional window of the group of oneor more transitional windows, forming an additional transitional windowthat includes the original portion of the targeted message, and addingthe additional transitional window to the group of one or moretransitional windows to form an expanded group of two or moretransitional windows. Interest module 124 may send, to the informationdistribution system, the targeted message to be output for display atthe second group of one or more client devices. The targeted message isdisplayed such that only a single transitional window of the expandedgroup of two or more transitional windows is fully displayed at a giventime, such that a client device in the second group of one or moreclient devices is configured to individually and cyclically display eachtransitional window in the expanded group of two or more transitionalwindows during a period of time, and such that a transition between thetransitional windows of the expanded group of two or more transitionalwindows is a horizontal transition.

In other words, a user may select a trend on the social media platform.In some examples, the selected trend may have a connection to aparticular brand. For instance, an athlete may be a “trend” for making agame-winning play, and the athlete may have a contract with a particularbrand of shoe that the athlete wears during games. As such, if a userselects the trend of the athlete to view messages drafted by usersdiscussing the athlete, the particular brand of shoe may draft theoriginal portion of the targeted message to include information aboutthe athlete's signature shoe sold by the particular brand of shoe. Thisoriginal portion of the targeted message may be included in one of thetransitional windows, and may be visible when the user who selected thetrend scrolls through the carousel portion of transitional windows.

In the example of FIG. 4A, user interface 402 is displayed on aparticular client device. User interface 402 includes trend list 404 andaccount messages 406A-406G, account messages 406A-406G shown in avertically scrolling message stream. At one point, the user of theclient device may provide an indication of user input selecting “AthleteA” as a trend. In other examples, a user may select any “trend” thatdescribes any topic that may be popular on the social media site.

After selecting the trend “Athlete A” a computing device, such ascomputing device 120 of FIG. 1, may send a targeted message to theclient device such that each transitional window of a carousel portionof the targeted message includes a different drafted message regardingthe trend. The carousel portion may also include an original portiondrafted by a user of computing device 120. Transitional window 408A maybe displayed initially, which includes a reaction to a play completed byAthlete A in a sporting event.

The transitional windows in the carousel portion of the targeted messagemay scroll horizontally, in contrast to the vertical scrolling ofaccount messages 406A-406G. In some examples, while the targeted messageis being displayed, account messages 406A-406G may be static,restricting the vertical scrolling in favor of the distinguishablehorizontal scrolling of the transitional windows.

In the example of FIG. 4B, the client device horizontally transitionedto show transitional window 408B. Transitional window 408B includes theoriginal portion of the targeted message, drafted by a particular brandof shoe that is associated with computing device 120 or by a marketingcompany hired by the particular brand of shoe. The original portion intransitional window 408B encourages the user to view Athlete A'ssignature shoe, capitalizing on Athlete A's current newsworthiness.

FIG. 5 is a flow diagram illustrating example operations of a computingdevice that implements techniques to create and output, for display atclient devices, targeted content that includes a carousel portion, inaccordance with one or more aspects of the present disclosure. Forpurposes of illustration only, the example operations are describedbelow within the context of computing device 120, as shown in FIGS. 1and 2.

Interest module 124 may receive (500) a first group of one or moremessages composed by a first group of one or more client devices frominformation distribution system 112, and store and organize the usercontent within computing device 120 at targeted content 126. Targetedcontent 126 may be stored and organized using any number of datastoresand data structures, such as but not limited to graphs, lists, tables, aRelational Database Management System (RDBMS), Object DatabaseManagement System (ODBMS), and/or Online Analytical Processing (OLAP)system.

Each of the messages received by interest module 124 of computing device120 may be composed by one or more users of the one or more clientdevices accessing a social media platform. Further, each of the messagesmay include a reference to a particular brand. For instance, in theexample of FIG. 5, the particular brand may, for purposes ofillustration only, be for a particular soft drink. As such, each of themessages may include a reference to the brand of the particular softdrink. For instance, a message may include any words describing theparticular brand, the particular soft drink itself, or any other marketidentifier that one would ordinarily associate with the particular brandor soft drink, such as a slogan for the soft drink or a trademarked wordor phrase. In some examples, information distribution system 112 mayonly send messages to computing device 120 that include the referencesto the particular brand. In other instances, information distributionsystem 112 may send a larger group of messages to computing device 120.In such instances, interest module 124 of computing device 120 may paredown the received group of messages by disregarding any messages that donot include reference to the particular brand.

The first group of one or more messages received by interest module 124may include a candidate message. Interest module 124 may determine(502), using a machine learning model, an interest score for thecandidate message based at least in part on content of the candidatemessage. In some instances, the interest score may be specific to a userof a client device that will receive a targeted message. In otherinstances, the interest score may be generally applicable to a group ofclient devices or all client devices. In general, the interest scorerepresents a likelihood that a user would interact with a targetedmessage if the targeted message included the candidate message as partof the targeted message's content. For instance, if the candidatemessage was drafted by a user of a social networking platform that isnot influential (e.g., the user does not have a large number ofsubscribers to their social media account), or the content of thecandidate message includes multiple grammatical errors, then interestmodule 124 may determine that the interest score for the candidatemessage is low. Conversely, if the candidate message was drafted by auser of a social networking platform that is very influential (e.g., theuser has millions of subscribers to their social media account, like acelebrity), and the content of the candidate message is creative,well-crafted, and grammatically sound, then interest module 124 maydetermine that the interest score is very high.

In general, the interest score may be indicative of a strength of arelation between the content of the candidate message and a particularproduct belonging to the particular brand. In other words, if thecontent of the candidate message closely describes or directlyreferences a product of the particular brand or the particular brand ingeneral, interest module 124 may determine a relatively higher interestscore for the candidate message. Conversely, if the content of thecandidate message does not reference the particular brand or looselyreferences the market to which the particular brand belongs, theninterest module 124 may determine a relatively lower interest score.

In some examples, interest module 124 may incorporate secondaryinformation stored in secondary information 230 when determining theinterest score. For instance, secondary information for the candidatemessage may include an author of the candidate message, a number ofsubscribers to a social media account of the author of the candidatemessage, a probability that a user of a client device of the secondgroup of one or more client devices will engage with the candidatemessage, an interaction history between the user of the client device ofthe second group of one or more client devices and the author of thecandidate message, a time that the candidate message was authored, ageolocation of a client device of the first group of one or more clientdevices used by the author of the candidate message to post thecandidate message, or a topic of the candidate message. Interest module124 may utilize the secondary information to determine the interestscore for the candidate message.

For instance, if the candidate message is authored by a famous user witha large number of subscribers, was authored by a user with similarinterests to the targeted user, was authored by a user who the targeteduser has interacted with in the past, was composed recently, wascomposed at a geographical location close to a geolocation of thetargeted user, or is regarding a topic of interest to the targeted user,interest module 124 may increase the interest score for the candidatemessage. Conversely, if the candidate message is authored by apedestrian user with a small number of subscribers, was authored by auser with different interests than the targeted user, was authored by auser who the targeted user has never interacted with in the past, wascomposed multiple years prior to the current date, was composed at ageographical location far away from a geolocation of the targeted user,or is regarding a topic that does not interest the targeted user,interest module 124 may decrease the interest score for the candidatemessage.

In some instances, upon determining the interest score, interest module124 may save an indication of the interest score for the candidatemessage in machine learning model 234. Interest module 124 may referencemachine learning model 234 in future instances of determining theinterest score for the candidate message.

Interest module 124 may determine (504) whether the interest scoresatisfies a threshold interest score. For instance, in the examplescenario of FIG. 5, a celebrity with a large number of subscribers totheir social media account may generate a candidate message thatincludes a creative and favorable reference to the particular brand ofsoft drink. The candidate message may also include media, such as apicture, an animated image file, or a video. Based on this information,interest module 124 may determine that the candidate message has a highinterest score that satisfies a threshold interest score (“YES” branchof 504). Responsive to this determination, message assembly module 220may insert (506) the candidate message into a group of one or more brandmessages. Each brand message in the group of one or more brand messagesincludes a reference to the particular brand. In other words, each ofthe brand messages is a candidate message that references the particularbrand and has an interest score that satisfies the previously referencedthreshold interest score.

Conversely, a user with very few subscribers to their social mediaaccount may generate a candidate message that includes a negativereference to the particular brand of soft drink, or a positive referenceto the particular brand of soft drink but with numerous typographicalerrors. Based on this information, interest module 124 may determinethat the candidate message has a low interest score that does notsatisfy the threshold interest score. Responsive to this determination,message assembly module 220 may refrain from inserting the candidatemessage into the group of one or more brand messages and determine (“NO”branch of 502) an interest score for a subsequent candidate message.

Message assembly module 220 may send (508), to information distributionsystem 112, a targeted message to be output for display at client device102A. The targeted message may include an original portion and acarousel portion. The original portion may merely include content formedat computing device 120. The carousel portion may include a group of oneor more transitional windows, where each transitional window in thegroup of one or more transitional windows includes one of the brandmessages in the group of one or more brand messages. Each of the one ormore transitional windows contain user-generated content, enablingclient device 102A to show multiple user-generated endorsements ofand/or media describing a specific product or brand. Such targetedcontent may provide users of client device 102A with a compact yetdetailed message that includes both content formed at computing device120 and a series of user-generated content referencing a particularproduct, brand, or market.

For the targeted message, each transitional window of the group of oneor more transitional windows may include a distinct graphical elementthat contains a respective brand message of the group of one or morebrand messages and information identifying a user who composed therespective brand message. For instance, the candidate message describedabove (i.e., the candidate message that satisfies the threshold interestscore) may have a designated transitional window to display the contentof the candidate message and information identifying the author of thecandidate message. Each remaining transitional window may include aseparate brand message where interest module 124 determined that thebrand message satisfied the threshold interest score. The carouselportion that contains the transitional windows may displayed within thetargeted message such that only a single transitional window of thegroup of one or more transitional windows is fully displayed at a giventime. A client device in the second group of one or more client devicesis configured to individually and cyclically display each transitionalwindow in the group of one or more transitional windows during a periodof time. The original portion may be displayed within the targetedmessage statically. The original portion may be content created,generated, or inserted by a user of computing device 120.

In some examples, the client device of the second group of one or moreclient devices that displays the targeted message may cycle through thevarious transitional windows. In some instances, the client device maycycle the carousel portion automatically after a predetermined amount oftime such that a different transitional window of the group of one ormore transitional windows is shown in a graphical user interface at theclient device. For instance, each transitional window may be displayedfor a certain time, such as three to five seconds, before cycling to adifferent transitional window.

In other instances, the client device may cycle the carousel portionresponsive to receiving an indication of user input at the client devicesuch that a different transitional window of the group of one or moretransitional windows is shown in a graphical user interface at theclient device. In other words, the user of the client device may providesome indication of user input, such as a tap or a swipe gesture, tocycle through the various transitional windows in the carousel portionof the targeted message.

In some examples, a brand message in the group of one or more brandmessages used to create the one or more transitional windows in thecarousel portion of the message may include various forms of media thatmay be displayed at the client device that receives the targetedmessage. In some instances, the media may include one of a video, apicture, or an animated image file. In the instances where the mediaincludes the audio, the video, or the animated image file, the clientdevice that outputs the targeted message for display may automaticallyplay the included media file when the client device displays thetransitional window that includes the brand message with the given mediafile.

The original portion of the targeted message may include contentgenerated by a user of computing device 120 describing the particularbrand of soft drink. Message assembly module 220 may further includemultiple transitional windows in the targeted message. One suchtransitional window may include the candidate message drafted by thecelebrity with a large numbers of subscribers to their social mediaaccount. Other transitional windows may include other brand messagesthat satisfy the threshold interest score. Client device 102A may outputthe targeted message such that the original portion of the targetedmessage is static in the graphical user interface. Client device 102Amay output the carousel portion such that a single transitional windowis fully visible, but also such that client device 102A may transitionbetween the transitional windows dynamically, either automatically aftera certain amount of time or in response to receiving an indication ofuser input. This allows multiple additional pieces of content to bepresent in a single message without excessively wasting area on thegraphical user interface at client device 102A. By including the groupof transitional windows that each include separate brand messages, eachof which may further include media, computing device 120 may increasethe effectiveness of targeted messages by increasing the amount andvariety of the content within the content provider's targeted messageswithout necessarily crowding the graphical user interface with largermessage windows.

In some instances, the user of the client device that receives thetargeted message may engage with the targeted message, such as viewingthe media included in the targeted message, disseminating the targetedmessage to one or more subscribers of a social media account associatedwith the targeted message, viewing the targeted message, or visiting awebpage from a hyperlink present in the targeted message. In suchinstances, interest module 124 may receive, from informationdistribution system 112, an indication that the user of the clientdevice of the second group of one or more client devices engaged withthe targeted message. In some instances, responsive to receiving theindication that the user of the client device of the second group of oneor more client devices engaged with the targeted message, interestmodule 124 may update the data stored in machine learning model 234 toindicate that the user of the client device engaged with the targetedmessage. In doing so, interest module 124 may increase the interestscore in machine learning model 234 such that similar targeted messagesare sent to the client device in the future. Conversely, if interestmodule 124 does not receive an indication that the user engaged with thetargeted message, interest module 124 may decrease the interest score inmachine learning model 234 such that different targeted messages aresent to the client device in the future.

In some instances, credit account 232 associated with computing device120 may profit from users engaging with targeted messages. In suchinstances, responsive to receiving the indication that the user of theclient device of the second group of one or more client devices engagedwith the targeted message, credit account 232 of computing device 120may receive a credit from an account associated with informationdistribution system 112. The credit may be monetary or some other pointor note, either of monetary value or of no monetary value.

In some examples, prior to the receipt of the first group of one or moremessages, computing device 120 may initially receive an indication ofuser input from a particular client device of the second group of one ormore client devices that indicates a selection of a trend that may berelated to the particular brand. As such, each of the messages in thefirst group of one or more messages includes content associated with thetrend. As such, interest module 124 may construct the carousel portionof the targeted message by placing a distinct graphical element thatcontains a respective brand message of the group of one or more brandmessages and information identifying a user who composed the respectivebrand message into a respective transitional window of the group of oneor more transitional windows, forming an additional transitional windowthat includes the original portion of the targeted message, and addingthe additional transitional window to the group of one or moretransitional windows to form an expanded group of two or moretransitional windows. Interest module 124 may send, to the informationdistribution system, the targeted message to be output for display atthe particular client device of the second group of one or more clientdevices. The targeted message is displayed such that only a singletransitional window of the expanded group of two or more transitionalwindows is fully displayed at a given time, such that the particularclient device of the second group of one or more client devices isconfigured to individually and cyclically display each transitionalwindow in the expanded group of two or more transitional windows duringa period of time, and such that a transition between the transitionalwindows of the expanded group of two or more transitional windows is ahorizontal transition.

In other words, a user may select a trend on the social media platform,or a particular subject that a large portion of accounts on the socialmedia platform (either globally or at some granularity of locality) areincluding in messages dispersed via the social media platform at arelatively same time (e.g., within a particular time frame of oneanother). In some examples, the selected trend may have a connection toa particular brand. For instance, an athlete may be a “trend” for makinga game-winning play, and the athlete may have a contract with aparticular brand of shoe that the athlete wears during games. As such,if a user selects the trend of the athlete to view messages drafted byusers discussing the athlete, the particular brand of shoe may draft theoriginal portion of the targeted message to include information aboutthe athlete's signature shoe sold by the particular brand of shoe. Thisoriginal portion of the targeted message may be included in one of thetransitional windows, and may be visible when the user who selected thetrend scrolls through the carousel portion of transitional windows.

Example 1

A method comprising: receiving, by a computing device and from aninformation distribution system, a first group of one or more messagescomposed by one or more users of a first group of one or more clientdevices accessing a social media platform, wherein each of the messagesin the first group of one or more messages includes a reference to aparticular brand; determining, by the computing device, using a machinelearning model, an interest score for a candidate message based at leastin part on content of the candidate message, wherein the candidatemessage is included in the first group of one or more messages;responsive to determining that the interest score satisfies a thresholdinterest score, inserting, by the computing device, the candidatemessage into a group of one or more brand messages, wherein each brandmessage in the group of one or more brand messages includes a referenceto the particular brand; and sending, by the computing device and to theinformation distribution system, a targeted message to be output fordisplay at a second group of one or more client devices, wherein thetargeted message comprises an original portion and a carousel portion,wherein the carousel portion comprises a group of one or moretransitional windows, wherein each transitional window in the group ofone or more transitional windows includes one of the brand messages inthe group of one or more brand messages, and wherein the originalportion comprises content formed at the computing device.

Example 2

The method of example 1, wherein determining the interest scorecomprises: determining, by the computing device, a strength of arelation between the content of the candidate message and a particularproduct belonging to the particular brand; and determining, by thecomputing device and based at least in part on the strength of therelation between the content of the candidate message and the particularproduct belonging to the particular brand, the interest score.

Example 3

The method of any of examples 1-2, wherein each transitional window ofthe group of one or more transitional windows comprises a distinctgraphical element that contains a respective brand message of the groupof one or more brand messages and information identifying a user whocomposed the respective brand message, wherein the original portion isdisplayed within the targeted message statically, and wherein thecarousel portion is displayed within the targeted message such that onlya single transitional window of the group of one or more transitionalwindows is fully displayed at a given time, such that a client device inthe second group of one or more client devices is configured toindividually and cyclically display each transitional window in thegroup of one or more transitional windows during a period of time, andsuch that the transition between the group of one or more transitionalwindows is a horizontal transition.

Example 4

The method of example 3, further comprising: cycling, by a client deviceof the second group of one or more client devices, the carousel portionautomatically after a predetermined amount of time such that a differenttransitional window of the group of one or more transitional windows isshown in a graphical user interface at the client device.

Example 5

The method of any of examples 3-4, further comprising: cycling, by aclient device of the second group of one or more client devices, thecarousel portion responsive to receiving an indication of user input atthe client device such that a different transitional window of the groupof one or more transitional windows is shown in a graphical userinterface at the client device.

Example 6

The method of any of examples 1-5, wherein a brand message in the groupof one or more brand messages includes media comprising one of audio, avideo, a picture, or an animated image file, and wherein the media isautomatically played upon display of the respective transitional windowof the group of one or more transitional windows that contains the brandmessage.

Example 7

The method of any of examples 1-6, further comprising: initiallyreceiving, by the computing device, an indication of user input from aparticular client device of the second group of one or more clientdevices that indicates a selection of a trend, wherein the trend isrelated to the particular brand, and wherein each of the messages in thefirst group of one or more messages includes content associated with thetrend; constructing, by the computing device, the carousel portion ofthe targeted message by: placing a distinct graphical element thatcontains a respective brand message of the group of one or more brandmessages and information identifying a user who composed the respectivebrand message into a respective transitional window of the group of oneor more transitional windows, forming an additional transitional windowthat includes the original portion of the targeted message, and addingthe additional transitional window to the group of one or moretransitional windows to form an expanded group of two or moretransitional windows; and sending, by the computing device and to theinformation distribution system, the targeted message to be output fordisplay at the particular client device of the second group of one ormore client devices, wherein the targeted message is displayed such thatonly a single transitional window of the expanded group of two or moretransitional windows is fully displayed at a given time, such that theparticular client device of the second group of one or more clientdevices is configured to individually and cyclically display eachtransitional window in the expanded group of two or more transitionalwindows during a period of time, and such that a transition between thetransitional windows of the expanded group of two or more transitionalwindows is a horizontal transition.

Example 8

The method of any of examples 1-7, further comprising: determining, bythe computing device, secondary information for the candidate message,wherein the secondary information comprises one or more of: an author ofthe candidate message, a number of subscribers to a social media accountof the author of the candidate message, a probability that a user of aclient device of the second group of one or more client devices willengage with the candidate message, an interaction history between theuser of the client device of the second group of one or more clientdevices and the author of the candidate message, a time that thecandidate message was authored, a geolocation of a client device of thefirst group of one or more client devices used by the author of thecandidate message to post the candidate message, or a topic of thecandidate message; and determining, by the computing device based atleast in part on the content of the candidate message and the secondaryinformation for the candidate message, the interest score.

Example 9

The method of any of examples 1-8, further comprising: receiving, by thecomputing device and from the information distribution system, anindication that a user of a client device of the second group of one ormore client devices engaged with the targeted message, wherein engagingwith the targeted message comprises one of viewing the targeted message,disseminating the targeted message to one or more subscribers of asocial media account associated with the user, or interacting with oneor more hyperlinks included in the targeted message; and updating, bythe computing device, the machine learning model to indicate that theuser of the client device of the second group of client devices engagedwith the targeted message.

Example 10

The method of example 9, further comprising: responsive to receiving theindication that the user of the client device of the second group of oneor more client devices engaged with the targeted message, receiving, byan account associated with the computing device, a credit from anaccount associated with the information distribution system.

Example 11

The method of any of examples 1-10, wherein sending the targeted messageto the information distribution system comprises sending, by thecomputing device and to the information distribution system, a messagestream to be output for display at a particular client device of thesecond group of one or more client devices, wherein the message streamcomprises a plurality of messages that includes the targeted message,wherein the message stream is configured to be output for display suchthat respective graphical indications of the plurality of messages inthe message stream are vertically scrollable, and wherein the carouselportion of the targeted message within the message stream is displayedsuch that the one or more transitional windows are horizontallyscrollable.

Example 12

A non-transitory computer-readable storage medium storing instructionsthat, when executed, cause at least one processor of a computing deviceto: receive, from an information distribution system, a first group ofone or more messages composed by one or more users of a first group ofone or more client devices accessing a social media platform, whereineach of the messages in the first group of one or more messages includesa reference to a particular brand; determine, using a machine learningmodel, an interest score for a candidate message based at least in parton content of the candidate message, wherein the candidate message isincluded in the first group of one or more messages; responsive todetermining that the interest score satisfies a threshold interestscore, insert the candidate message into a group of one or more brandmessages, wherein each brand message in the group of one or more brandmessages includes a reference to the particular brand; and send, to theinformation distribution system, a targeted message to be output fordisplay at a second group of one or more client devices, wherein thetargeted message comprises an original portion and a carousel portion,wherein the carousel portion comprises a group of one or moretransitional windows, wherein each transitional window in the group ofone or more transitional windows includes one of the brand messages inthe group of one or more brand messages, and wherein the originalportion comprises content formed at the computing device.

Example 13

The non-transitory computer-readable storage medium of example 12,wherein the instructions that cause the at least one processor todetermine the interest score comprise instructions that, when executed,cause the at least one processor to: determine a strength of a relationbetween the content of the candidate message and a particular productbelonging to the particular brand; and determine, based at least in parton the strength of the relation between the content of the candidatemessage and the particular product belonging to the particular brand,the interest score.

Example 14

The non-transitory computer-readable storage medium of any of examples12-13, wherein each transitional window of the group of one or moretransitional windows comprises a distinct graphical element thatcontains a respective brand message of the group of one or more brandmessages and information identifying a user who composed the respectivebrand message, wherein the original portion is displayed within thetargeted message statically, and wherein the carousel portion isdisplayed within the targeted message such that only a singletransitional window of the group of one or more transitional windows isfully displayed at a given time, such that a client device in the secondgroup of one or more client devices is configured to individually andcyclically display each transitional window in the group of one or moretransitional windows during a period of time, and such that thetransition between the group of one or more transitional windows is ahorizontal transition.

Example 15

The non-transitory computer-readable storage medium of example 14,further comprising instructions that, when executed, cause the at leastone processor to: cycle the carousel portion automatically after apredetermined amount of time such that a different transitional windowof the group of one or more transitional windows is shown in a graphicaluser interface at the client device.

Example 16

The non-transitory computer-readable storage medium of any of examples14-15, further comprising instructions that, when executed, cause the atleast one processor to: cycle the carousel portion responsive toreceiving an indication of user input at the client device such that adifferent transitional window of the group of one or more transitionalwindows is shown in a graphical user interface at the client device.

Example 17

The non-transitory computer-readable storage medium of any of examples12-16, wherein a brand message in the group of one or more brandmessages includes media comprising one of audio, a video, a picture, oran animated image file, and wherein the media is automatically playedupon display of the respective transitional window of the group of oneor more transitional windows that contains the brand message.

Example 18

The non-transitory computer-readable storage medium of any of examples12-17, further comprising instructions that, when executed, cause the atleast one processor to: initially receive an indication of user inputfrom a particular client device of the second group of one or moreclient devices that indicates a selection of a trend, wherein the trendis related to the particular brand, and wherein each of the messages inthe first group of one or more messages includes content associated withthe trend; construct the carousel portion of the targeted message by:placing a distinct graphical element that contains a respective brandmessage of the group of one or more brand messages and informationidentifying a user who composed the respective brand message into arespective transitional window of the group of one or more transitionalwindows, forming an additional transitional window that includes theoriginal portion of the targeted message, and adding the additionaltransitional window to the group of one or more transitional windows toform an expanded group of two or more transitional windows; and send, tothe information distribution system, the targeted message to be outputfor display at the particular client device of the second group of oneor more client devices, wherein the targeted message is displayed suchthat only a single transitional window of the expanded group of two ormore transitional windows is fully displayed at a given time, such thatthe particular client device of the second group of one or more clientdevices is configured to individually and cyclically display eachtransitional window in the expanded group of two or more transitionalwindows during a period of time, and such that a transition between thetransitional windows of the expanded group of two or more transitionalwindows is a horizontal transition.

Example 19

The non-transitory computer-readable storage medium of any of examples12-18, further comprising instructions that, when executed, cause the atleast one processor to: determine secondary information for thecandidate message, wherein the secondary information comprises one ormore of: an author of the candidate message, a number of subscribers toa social media account of the author of the candidate message, aprobability that a user of a client device of the second group of one ormore client devices will engage with the candidate message, aninteraction history between the user of the client device of the secondgroup of one or more client devices and the author of the candidatemessage, a time that the candidate message was authored, a geolocationof a client device of the first group of one or more client devices usedby the author of the candidate message to post the candidate message, ora topic of the candidate message; and determine, based at least in parton the content of the candidate message and the secondary informationfor the candidate message, the interest score.

Example 20

The non-transitory computer-readable storage medium of any of examples12-19, further comprising instructions that, when executed, cause the atleast one processor to: receive, from the information distributionsystem, an indication that a user of a client device of the second groupof one or more client devices engaged with the targeted message, whereinengaging with the targeted message comprises one of viewing the targetedmessage, disseminating the targeted message to one or more subscribersof a social media account associated with the user, or interacting withone or more hyperlinks included in the targeted message; and update themachine learning model to indicate that the user of the client device ofthe second group of client devices engaged with the targeted message.

Example 21

The non-transitory computer-readable storage medium of example 20,further comprising instructions that, when executed, cause the at leastone processor to: responsive to receiving the indication that the userof the client device of the second group of one or more client devicesengaged with the targeted message, receive, by an account associatedwith the computing device, a credit from an account associated with theinformation distribution system.

Example 22

The non-transitory computer-readable storage medium of any of examples12-21, wherein the instructions that cause the at least one processor tosend the targeted message to the information distribution systemcomprise instructions that, when executed, further cause the at leastone processor to send, to the information distribution system, a messagestream to be output for display at a particular client device of thesecond group of one or more client devices, wherein the message streamcomprises a plurality of messages that includes the targeted message,wherein the message stream is configured to be output for display suchthat respective graphical indications of the plurality of messages inthe message stream are vertically scrollable, and wherein the carouselportion of the targeted message within the message stream is displayedsuch that the one or more transitional windows are horizontallyscrollable.

Example 23

A computing device comprising: at least one processor; and at least onenon-transitory computer-readable storage medium storing instructionsthat are executable by the at least one processor to: receive, from aninformation distribution system, a first group of one or more messagescomposed by one or more users of a first group of one or more clientdevices accessing a social media platform, wherein each of the messagesin the first group of one or more messages includes a reference to aparticular brand; determine, using a machine learning model, an interestscore for a candidate message based at least in part on content of thecandidate message, wherein the candidate message is included in thefirst group of one or more messages; responsive to determining that theinterest score satisfies a threshold interest score, insert thecandidate message into a group of one or more brand messages, whereineach brand message in the group of one or more brand messages includes areference to the particular brand; and send, to the informationdistribution system, a targeted message to be output for display at asecond group of one or more client devices, wherein the targeted messagecomprises an original portion and a carousel portion, wherein thecarousel portion comprises a group of one or more transitional windows,wherein each transitional window in the group of one or moretransitional windows includes one of the brand messages in the group ofone or more brand messages, and wherein the original portion comprisescontent formed at the computing device.

Example 24

The computing device of example 23, wherein the instructions that areexecutable by the at least one processor to determine the interest scorecomprise instructions that are executable by the at least one processorto: determine a strength of a relation between the content of thecandidate message and a particular product belonging to the particularbrand; and determine, based at least in part on the strength of therelation between the content of the candidate message and the particularproduct belonging to the particular brand, the interest score.

Example 25

The computing device of any of examples 23-24, wherein each transitionalwindow of the group of one or more transitional windows comprises adistinct graphical element that contains a respective brand message ofthe group of one or more brand messages and information identifying auser who composed the respective brand message, wherein the originalportion is displayed within the targeted message statically, and whereinthe carousel portion is displayed within the targeted message such thatonly a single transitional window of the group of one or moretransitional windows is fully displayed at a given time, such that aclient device in the second group of one or more client devices isconfigured to individually and cyclically display each transitionalwindow in the group of one or more transitional windows during a periodof time, and such that the transition between the group of one or moretransitional windows is a horizontal transition.

Example 26

The computing device of example 25, wherein the non-transitorycomputer-readable storage medium further stores instructions that areexecutable by the at least one processor to: cycle the carousel portionautomatically after a predetermined amount of time such that a differenttransitional window of the group of one or more transitional windows isshown in a graphical user interface at the client device.

Example 27

The computing device of any of examples 25-26, wherein thenon-transitory computer-readable storage medium further storesinstructions that are executable by the at least one processor to: cyclethe carousel portion responsive to receiving an indication of user inputat the client device such that a different transitional window of thegroup of one or more transitional windows is shown in a graphical userinterface at the client device.

Example 28

The computing device of any of examples 23-27, further comprisinginstructions executable by the at least one processor to: initiallyreceive an indication of user input from a particular client device ofthe second group of one or more client devices that indicates aselection of a trend, wherein the trend is related to the particularbrand, and wherein each of the messages in the first group of one ormore messages includes content associated with the trend; construct thecarousel portion of the targeted message by: placing a distinctgraphical element that contains a respective brand message of the groupof one or more brand messages and information identifying a user whocomposed the respective brand message into a respective transitionalwindow of the group of one or more transitional windows, forming anadditional transitional window that includes the original portion of thetargeted message, and adding the additional transitional window to thegroup of one or more transitional windows to form an expanded group oftwo or more transitional windows; and send, to the informationdistribution system, the targeted message to be output for display atthe particular client device of the second group of one or more clientdevices, wherein the targeted message is displayed such that only asingle transitional window of the expanded group of two or moretransitional windows is fully displayed at a given time, such that theparticular client device of the second group of one or more clientdevices is configured to individually and cyclically display eachtransitional window in the expanded group of two or more transitionalwindows during a period of time, and such that a transition between thetransitional windows of the expanded group of two or more transitionalwindows is a horizontal transition.

Example 29

The computing device of any of examples 23-28, wherein thenon-transitory computer-readable storage medium further storesinstructions that are executable by the at least one processor to:determine secondary information for the candidate message, wherein thesecondary information comprises one or more of: an author of thecandidate message, a number of subscribers to a social media account ofthe author of the candidate message, a probability that a user of aclient device of the second group of one or more client devices willengage with the candidate message, an interaction history between theuser of the client device of the second group of one or more clientdevices and the author of the candidate message, a time that thecandidate message was authored, a geolocation of a client device of thefirst group of one or more client devices used by the author of thecandidate message to post the candidate message, or a topic of thecandidate message; and determine, based at least in part on the contentof the candidate message and the secondary information for the candidatemessage, the interest score.

Example 30

The computing device of any of examples 23-29, wherein thenon-transitory computer-readable storage medium further storesinstructions that are executable by the at least one processor to:receive, from the information distribution system, an indication that auser of a client device of the second group of one or more clientdevices engaged with the targeted message, wherein engaging with thetargeted message comprises one of viewing the targeted message,disseminating the targeted message to one or more subscribers of asocial media account associated with the user, or interacting with oneor more hyperlinks included in the targeted message; update the machinelearning model to indicate that the user of the client device of thesecond group of client devices engaged with the targeted message; andresponsive to receiving the indication that the user of the clientdevice of the second group of one or more client devices engaged withthe targeted message, receive, by an account associated with thecomputing device, a credit from an account associated with theinformation distribution system.

Example 31

A device comprising means for performing the method of any of examples1-11.

Example 32

A non-transitory computer-readable storage medium storing instructionsthat, when executed, cause at least one processor to perform the methodof any of examples 1-11.

Example 33

A device comprising at least one module operable by one or moreprocessors to perform the method of any of examples 1-11.

In one or more examples, the functions described may be implemented inhardware, software, firmware, or any combination thereof. If implementedin software, the functions may be stored on or transmitted over, as oneor more instructions or code, a computer-readable medium and executed bya hardware-based processing unit. Computer-readable media may includecomputer-readable storage media, which corresponds to a tangible mediumsuch as data storage media, or communication media including any mediumthat facilitates transfer of a computer program from one place toanother, e.g., according to a communication protocol. In this manner,computer-readable media generally may correspond to (1) tangiblecomputer-readable storage media, which is non-transitory or (2) acommunication medium such as a signal or carrier wave. Data storagemedia may be any available media that can be accessed by one or morecomputers or one or more processors to retrieve instructions, codeand/or data structures for implementation of the techniques described inthis disclosure. A computer program product may include acomputer-readable medium.

By way of example, and not limitation, such computer-readable storagemedia can comprise RAM, ROM, EEPROM, CD-ROM or other optical diskstorage, magnetic disk storage, or other magnetic storage devices, flashmemory, or any other medium that can be used to store desired programcode in the form of instructions or data structures and that can beaccessed by a computer. Also, any connection is properly termed acomputer-readable medium. For example, if instructions are transmittedfrom a website, server, or other remote source using a coaxial cable,fiber optic cable, twisted pair, digital subscriber line (DSL), orwireless technologies such as infrared, radio, and microwave, then thecoaxial cable, fiber optic cable, twisted pair, DSL, or wirelesstechnologies such as infrared, radio, and microwave are included in thedefinition of medium. It should be understood, however, thatcomputer-readable storage media and data storage media do not includeconnections, carrier waves, signals, or other transient media, but areinstead directed to non-transient, tangible storage media. Disk anddisc, as used, includes compact disc (CD), laser disc, optical disc,digital versatile disc (DVD), floppy disk and Blu-ray disc, where disksusually reproduce data magnetically, while discs reproduce dataoptically with lasers. Combinations of the above should also be includedwithin the scope of computer-readable media.

Instructions may be executed by one or more processors, such as one ormore digital signal processors (DSPs), general purpose microprocessors,application specific integrated circuits (ASICs), field programmablelogic arrays (FPGAs), or other equivalent integrated or discrete logiccircuitry. Accordingly, the term “processor,” as used may refer to anyof the foregoing structure or any other structure suitable forimplementation of the techniques described. In addition, in someaspects, the functionality described may be provided within dedicatedhardware and/or software modules. Also, the techniques could be fullyimplemented in one or more circuits or logic elements.

The techniques of this disclosure may be implemented in a wide varietyof devices or apparatuses, including a wireless handset, an integratedcircuit (IC) or a set of ICs (e.g., a chip set). Various components,modules, or units are described in this disclosure to emphasizefunctional aspects of devices configured to perform the disclosedtechniques, but do not necessarily require realization by differenthardware units. Rather, as described above, various units may becombined in a hardware unit or provided by a collection ofinteroperative hardware units, including one or more processors asdescribed above, in conjunction with suitable software and/or firmware.

It is to be recognized that depending on the embodiment, certain acts orevents of any of the methods described herein can be performed in adifferent sequence, may be added, merged, or left out altogether (e.g.,not all described acts or events are necessary for the practice of themethod). Moreover, in certain embodiments, acts or events may beperformed concurrently, e.g., through multi-threaded processing,interrupt processing, or multiple processors, rather than sequentially.

In some examples, a computer-readable storage medium includes anon-transitory medium. In some examples, the term “non-transitory”indicates that the storage medium is not embodied in a carrier wave or apropagated signal. In certain examples, a non-transitory storage mediummay store data that can, over time, change (e.g., in RAM or cache).Although certain examples are described as outputting variousinformation for display, techniques of the disclosure may output suchinformation in other forms, such as audio, holographical, or hapticforms, to name only a few examples, in accordance with techniques of thedisclosure.

Various examples of the disclosure have been described. Any combinationof the described systems, operations, or functions is contemplated.These and other examples are within the scope of the following claims.

What is claimed is:
 1. A method comprising: receiving, by a computingdevice and from an information distribution system, a first group of oneor more messages composed by one or more users of a first group of oneor more client devices accessing a social media platform, wherein eachof the messages in the first group of one or more messages includes areference to a particular brand; determining, by the computing device,using a machine learning model, an interest score for a candidatemessage based at least in part on content of the candidate message,wherein the candidate message is included in the first group of one ormore messages; responsive to determining that the interest scoresatisfies a threshold interest score, inserting, by the computingdevice, the candidate message into a group of one or more brandmessages, wherein each brand message in the group of one or more brandmessages includes a reference to the particular brand; and sending, bythe computing device and to the information distribution system, atargeted message to be output for display at a second group of one ormore client devices, wherein the targeted message comprises an originalportion and a carousel portion, wherein the carousel portion comprises agroup of two or more transitional windows, wherein each transitionalwindow in the group of two or more transitional windows includes one ofthe brand messages in the group of one or more brand messages, andwherein the original portion comprises content formed at the computingdevice, the method further comprising: initially receiving, by thecomputing device, an indication of user input from a particular clientdevice of the second group of one or more client devices that indicatesa selection of a trend, wherein the trend is related to the particularbrand, and wherein each of the messages in the first group of one ormore messages includes content associated with the trend; andconstructing, by the computing device, the carousel portion of thetargeted message by: placing a distinct graphical element that containsa respective brand message of the group of one or more brand messagesand information identifying a user who composed the respective brandmessage into a respective transitional window of the group of two ormore transitional windows, forming an additional transitional windowthat includes the original portion of the targeted message, and addingthe additional transitional window to the group of one or moretransitional windows to form an expanded group of three or moretransitional windows; and sending, by the computing device and to theinformation distribution system, the targeted message to be output fordisplay at the particular client device of the second group of one ormore client devices, wherein the targeted message is displayed such thatonly a single transitional window of the expanded group of three or moretransitional windows is fully displayed at a given time, such that theparticular client device of the second group of one or more clientdevices is configured to individually and cyclically display eachtransitional window in the expanded group of three or more transitionalwindows during a period of time, and such that a transition between thetransitional windows of the expanded group of three or more transitionalwindows is a horizontal transition.
 2. The method of claim 1, wherein abrand message in the group of two or more brand messages includes mediacomprising one of audio, a video, a picture, or an animated image file,and wherein the media is automatically played upon display of therespective transitional window of the group of two or more transitionalwindows that contains the brand message.
 3. The method of claim 1,further comprising: determining, by the computing device, secondaryinformation for the candidate message, wherein the secondary informationcomprises one or more of: an author of the candidate message, a numberof subscribers to a social media account of the author of the candidatemessage, a probability that a user of a client device of the secondgroup of one or more client devices will engage with the candidatemessage, an interaction history between the user of the client device ofthe second group of one or more client devices and the author of thecandidate message, a time that the candidate message was authored, ageolocation of a client device of the first group of one or more clientdevices used by the author of the candidate message to post thecandidate message, or a topic of the candidate message; and determining,by the computing device based at least in part on the content of thecandidate message and the secondary information for the candidatemessage, using the machine learning model, the interest score.
 4. Themethod of claim 1, further comprising: receiving, by the computingdevice and from the information distribution system, an indication thata user of a client device of the second group of one or more clientdevices engaged with the targeted message, wherein engaging with thetargeted message comprises one of viewing the targeted message,disseminating the targeted message to one or more subscribers of asocial media account associated with the user, or interacting with oneor more hyperlinks included in the targeted message; and updating, bythe computing device, the machine learning model to indicate that theuser of the client device of the second group of client devices engagedwith the targeted message.
 5. The method of claim 4, further comprising:responsive to receiving the indication that the user of the clientdevice of the second group of one or more client devices engaged withthe targeted message, receiving, by an account associated with thecomputing device, a credit from an account associated with theinformation distribution system.
 6. The method of claim 1, whereindetermining the interest score comprises: determining, by the computingdevice, a strength of a relation between the content of the candidatemessage and a particular product belonging to the particular brand; anddetermining, by the computing device and based at least in part on thestrength of the relation between the content of the candidate messageand the particular product belonging to the particular brand, theinterest score.
 7. The method of claim 1, further comprising: cycling,by a client device of the second group of one or more client devices,the carousel portion automatically after a predetermined amount of timesuch that a different transitional window of the expanded group of threeor more transitional windows is shown in a graphical user interface atthe client device.
 8. The method of claim 1, further comprising:cycling, by a client device of the second group of one or more clientdevices, the carousel portion responsive to receiving an indication ofuser input at the client device such that a different transitionalwindow of the expanded group of three or more transitional windows isshown in a graphical user interface at the client device.
 9. Anon-transitory computer-readable storage medium storing instructionsthat, when executed, cause at least one processor to: receive, from aninformation distribution system, a first group of one or more messagescomposed by one or more users of a first group of one or more clientdevices accessing a social media platform, wherein each of the messagesin the first group of one or more messages includes a reference to aparticular brand; determine, using a machine learning model, an interestscore for a candidate message based at least in part on content of thecandidate message, wherein the candidate message is included in thefirst group of one or more messages; responsive to determining that theinterest score satisfies a threshold interest score, insert thecandidate message into a group of one or more brand messages, whereineach brand message in the group of one or more brand messages includes areference to the particular brand; and send, to the informationdistribution system, a targeted message to be output for display at asecond group of one or more client devices, wherein the targeted messagecomprises an original portion and a carousel portion, wherein thecarousel portion comprises a group of two or more transitional windows,wherein each transitional window in the group of two or moretransitional windows includes one of the brand messages in the group ofone or more brand messages, and wherein the original portion comprisescontent formed at the computing device, the non-transitorycomputer-readable storage medium further comprising instructions that,when executed, cause the at least one processor to: initially receive anindication of user input from a particular client device of the secondgroup of one or more client devices that indicates a selection of atrend, wherein the trend is related to the particular brand, and whereineach of the messages in the first group of one or more messages includescontent associated with the trend; construct the carousel portion of thetargeted message by: placing a distinct graphical element that containsa respective brand message of the group of one or more brand messagesand information identifying a user who composed the respective brandmessage into a respective transitional window of the group of two ormore transitional windows, forming an additional transitional windowthat includes the original portion of the targeted message, and addingthe additional transitional window to the group of one or moretransitional windows to form an expanded group of three or moretransitional windows; and send, to the information distribution system,the targeted message to be output for display at the particular clientdevice of the second group of one or more client devices, wherein thetargeted message is displayed such that only a single transitionalwindow of the expanded group of three or more transitional windows isfully displayed at a given time, such that the particular client deviceof the second group of one or more client devices is configured toindividually and cyclically display each transitional window in theexpanded group of three or more transitional windows during a period oftime, and such that a transition between the transitional windows of theexpanded group of three or more transitional windows is a horizontaltransition.
 10. The non-transitory computer-readable storage medium ofclaim 9, wherein the instructions that cause the at least one processorto determine the interest score comprise instructions that, whenexecuted, cause the at least one processor to: determine a strength of arelation between the content of the candidate message and a particularproduct belonging to the particular brand; and determine, based at leastin part on the strength of the relation between the content of thecandidate message and the particular product belonging to the particularbrand, the interest score.
 11. The non-transitory computer-readablestorage medium of claim 9, further comprising instructions that, whenexecuted, cause the at least one processor to: cycle the carouselportion automatically after a predetermined amount of time such that adifferent transitional window of the group three or more transitionalwindows is shown in a graphical user interface at the client device. 12.The non-transitory computer-readable storage medium of claim 9, furthercomprising instructions that, when executed, cause the at least oneprocessor to: cycle the carousel portion responsive to receiving anindication of user input at the client device such that a differenttransitional window of the group of three or more transitional windowsis shown in a graphical user interface at the client device.
 13. Thenon-transitory computer-readable storage medium of claim 9, wherein abrand message in the group of one or more brand messages includes mediacomprising one of audio, a video, a picture, or an animated image file,and wherein the media is automatically played upon display of therespective transitional window of the group of two or more transitionalwindows that contains the brand message.
 14. The non-transitorycomputer-readable storage medium of claim 9, further comprisinginstructions that, when executed, cause the at least one processor to:determine secondary information for the candidate message, wherein thesecondary information comprises one or more of: an author of thecandidate message, a number of subscribers to a social media account ofthe author of the candidate message, a probability that a user of aclient device of the second group of one or more client devices willengage with the candidate message, an interaction history between theuser of the client device of the second group of one or more clientdevices and the author of the candidate message, a time that thecandidate message was authored, a geolocation of a client device of thefirst group of one or more client devices used by the author of thecandidate message to post the candidate message, or a topic of thecandidate message; and determine, based at least in part on the contentof the candidate message and the secondary information for the candidatemessage, using the machine learning model, the interest score.
 15. Thenon-transitory computer-readable storage medium of claim 9, furthercomprising instructions that, when executed, cause the at least oneprocessor to: receive, from the information distribution system, anindication that a user of a client device of the second group of one ormore client devices engaged with the targeted message, wherein engagingwith the targeted message comprises one of viewing the targeted message,disseminating the targeted message to one or more subscribers of asocial media account associated with the user, or interacting with oneor more hyperlinks included in the targeted message; and update themachine learning model to indicate that the user of the client device ofthe second group of client devices engaged with the targeted message.16. The non-transitory computer-readable storage medium of claim 15,further comprising instructions that, when executed, cause the at leastone processor to: responsive to receiving the indication that the userof the client device of the second group of one or more client devicesengaged with the targeted message, receive, by an account associatedwith the computing device, a credit from an account associated with theinformation distribution system.
 17. A computing device comprising: atleast one processor; and at least one non-transitory computer-readablestorage medium storing instructions that are executable by the at leastone processor to: receive, from an information distribution system, afirst group of one or more messages composed by one or more users of afirst group of one or more client devices accessing a social mediaplatform, wherein each of the messages in the first group of one or moremessages includes a reference to a particular brand; determine, using amachine learning model, an interest score for a candidate message basedat least in part on content of the candidate message, wherein thecandidate message is included in the first group of one or moremessages; responsive to determining that the interest score satisfies athreshold interest score, insert the candidate message into a group ofone or more brand messages, wherein each brand message in the group ofone or more brand messages includes a reference to the particular brand;and send, to the information distribution system, a targeted message tobe output for display at a second group of one or more client devices,wherein the targeted message comprises an original portion and acarousel portion, wherein the carousel portion comprises a group of twoor more transitional windows, wherein each transitional window in thegroup of two or more transitional windows includes one of the brandmessages in the group of one or more brand messages, and wherein theoriginal portion comprises content formed at the computing device, thecomputing device further comprising instructions executable by the atleast one processor to: initially receive an indication of user inputfrom a particular client device of the second group of one or moreclient devices that indicates a selection of a trend, wherein the trendis related to the particular brand, and wherein each of the messages inthe first group of one or more messages includes content associated withthe trend; construct the carousel portion of the targeted message by:placing a distinct graphical element that contains a respective brandmessage of the group of one or more brand messages and informationidentifying a user who composed the respective brand message into arespective transitional window of the group of two or more transitionalwindows, forming an additional transitional window that includes theoriginal portion of the targeted message, and adding the additionaltransitional window to the group of one or more transitional windows toform an expanded group of three or more transitional windows; and send,to the information distribution system, the targeted message to beoutput for display at the particular client device of the second groupof one or more client devices, wherein the targeted message is displayedsuch that only a single transitional window of the expanded group ofthree or more transitional windows is fully displayed at a given time,such that the particular client device of the second group of one ormore client devices is configured to individually and cyclically displayeach transitional window in the expanded group of three or moretransitional windows during a period of time, and such that a transitionbetween the transitional windows of the expanded group of three or moretransitional windows is a horizontal transition.
 18. The computingdevice of claim 17, wherein the instructions that are executable by theat least one processor to determine the interest score compriseinstructions that are executable by the at least one processor to:determine a strength of a relation between the content of the candidatemessage and a particular product belonging to the particular brand; anddetermine, based at least in part on the strength of the relationbetween the content of the candidate message and the particular productbelonging to the particular brand, the interest score.
 19. The computingdevice of claim 17, wherein the non-transitory computer-readable storagemedium further stores instructions that are executable by the at leastone processor to: cycle the carousel portion automatically after apredetermined amount of time such that a different transitional windowof the group of three or more transitional windows is shown in agraphical user interface at the client device.
 20. The computing deviceof claim 17, wherein the non-transitory computer-readable storage mediumfurther stores instructions that are executable by the at least oneprocessor to: cycle the carousel portion responsive to receiving anindication of user input at the client device such that a differenttransitional window of the group of three or more transitional windowsis shown in a graphical user interface at the client device.
 21. Thecomputing device of claim 17, wherein the non-transitorycomputer-readable storage medium further stores instructions that areexecutable by the at least one processor to: determine secondaryinformation for the candidate message, wherein the secondary informationcomprises one or more of: an author of the candidate message, a numberof subscribers to a social media account of the author of the candidatemessage, a probability that a user of a client device of the secondgroup of one or more client devices will engage with the candidatemessage, an interaction history between the user of the client device ofthe second group of one or more client devices and the author of thecandidate message, a time that the candidate message was authored, ageolocation of a client device of the first group of one or more clientdevices used by the author of the candidate message to post thecandidate message, or a topic of the candidate message; and determine,based at least in part on the content of the candidate message and thesecondary information for the candidate message, using the machinelearning model, the interest score.
 22. The computing device of claim17, wherein the non-transitory computer-readable storage medium furtherstores instructions that are executable by the at least one processorto: receive, from the information distribution system, an indicationthat a user of a client device of the second group of one or more clientdevices engaged with the targeted message, wherein engaging with thetargeted message comprises one of viewing the targeted message,disseminating the targeted message to one or more subscribers of asocial media account associated with the user, or interacting with oneor more hyperlinks included in the targeted message; update the machinelearning model to indicate that the user of the client device of thesecond group of client devices engaged with the targeted message; andresponsive to receiving the indication that the user of the clientdevice of the second group of one or more client devices engaged withthe targeted message, receive, by an account associated with thecomputing device, a credit from an account associated with theinformation distribution system.